A Resolution for Shared Memory Conflict in Multiprocessor System-on-a-Chip

Abstract: Now days, manufacturers are focusing on increasing the concurrency in multiprocessor system-on-a-chip (MPSoC) architecture instead of increasing clock speed, for embedded systems. Traditionally lock-based synchronization is provided to support concurrency; as managing locks can be very difficult and error prone. Transactional memories and lock based systems have been extensively used to provide synchronization between multiple processors [1] in general-purpose systems. It has been shown that locks have numerous shortcomings over transactional memory in terms of power consumption, ease of programming and performance. In this paper, we propose a new semaphore scheme for synchronization in shared cache memory in an MPSoC. Moreover, we have evaluated and compared our scheme with locks and transactions in terms of energy consumption and cache miss rate using SimpleScalar functional simulator.


Case Tool: Fast Interconnections with New 3-Disjoint Paths MIN Simulation Module

Abstract: Multi-stage interconnection networks (MIN) can be designed to achieve fault tolerance and collision solving by providing a set of disjoint paths. In this paper, we are discussing the new simulator added to the tool designed for developing fault tolerant MINs. The designed tool is one of its own kind and will help the user in developing 2 and 3-disjoint path networks. The java technology has been used to design the tool and have been tested on different software platform.


Classification of Flames in Computer Mediated Communications

Abstract: Computer Mediated Communication (CMC) has brought about a revolution in the way the world communicates with each other. With the increasing number of people, interacting through the internet and the rise of new platforms and technologies has brought together the people from different social, cultural and geographical backgrounds to present their thoughts, ideas and opinions on topics of their interest. CMC has, in some cases, gave users more freedom to express themselves as compared to Face-to-face communication. This has also led to rise in the use of hostile and aggressive language and terminologies uninhibitedly. Since such use of language is detrimental to the discussion process and affects the audience and individuals negatively, efforts are being taken to control them. The research sees the need to understand the concept of flaming and hence attempts to classify them in order to give a better understanding of it. The classification is done on the basis of type of flame content being presented and the Style in which they are presented.


Agile Research

Abstract: This paper discusses the application of agile software development methods in software-based research environments.


Influence of Topological Features on Spatially-Structured Evolutionary Algorithms Dynamics

Abstract: In the last decades, complex networks theory significantly influenced other disciplines on the modeling of both static and dynamic aspects of systems observed in nature. This work aims to investigate the effects of networks' topological features on the dynamics of an evolutionary algorithm, considering in particular the ability to find a large number of optima on multi-modal problems. We introduce a novel spatially-structured evolutionary algorithm and we apply it on two combinatorial problems: ONEMAX and the multi-modal NMAX. Considering three different network models we investigate the relationships between their features, algorithm's convergence and its ability to find multiple optima (for the multi-modal problem). In order to perform a deeper analysis we investigate the introduction of weighted graphs with time-varying weights. The results show that networks with a large Average Path Length lead to an higher number of optima and a consequent slow exploration dynamics (i.e. low First Hitting Time). Furthermore, the introduction of weighted networks shows the possibility to tune algorithm's dynamics during its execution with the parameter related with weights' change. This work gives a first answer about the effects of various graph topologies on the diversity of evolutionary algorithms and it describes a simple but powerful algorithmic framework which allows to investigate many aspects of ssEAs dynamics.


A non-local method for robustness analysis of floating point programs

Abstract: Robustness is a standard correctness property which intuitively means that if the input to the program changes less than a fixed small amount then the output changes only slightly. This notion is useful in the analysis of rounding error for floating point programs because it helps to establish bounds on output errors introduced by both measurement errors and by floating point computation. Compositional methods often do not work since key constructs---like the conditional and the while-loop---are not robust. We propose a method for proving the robustness of a while-loop. This method is non-local in the sense that instead of breaking the analysis down to single lines of code, it checks certain global properties of its structure. We show the applicability of our method on two standard algorithms: the CORDIC computation of the cosine and Dijkstra's shortest path algorithm.


The Game of Pure Strategy is solved!

Abstract: We solve the classical "Game of Pure Strategy" using linear programming. We notice an intricate even-odd behavior in the results of our computations, that seems to encourage odd or maximal bids.


Assessment of OGC Web Processing Services for REST principles

Abstract: Recent distributed computing trends advocate the use of Representational State Transfer (REST) to alleviate the inherent complexity of the Web services standards in building service-oriented web applications. In this paper we focus on the particular case of geospatial services interfaced by the OGC Web Processing Service (WPS) specification in order to assess whether WPS-based geospatial services can be viewed from the architectural principles exposed in REST. Our concluding remarks suggest that the adoption of REST principles, to specially harness the built-in mechanisms of the HTTP application protocol, may be beneficial in scenarios where ad hoc composition of geoprocessing services are required, common for most non-expert users of geospatial information infrastructures.


Joint Coding and Scheduling Optimization in Wireless Systems with Varying Delay Sensitivities

Abstract: Throughput and per-packet delay can present strong trade-offs that are important in the cases of delay sensitive applications.We investigate such trade-offs using a random linear network coding scheme for one or more receivers in single hop wireless packet erasure broadcast channels. We capture the delay sensitivities across different types of network applications using a class of delay metrics based on the norms of packet arrival times. With these delay metrics, we establish a unified framework to characterize the rate and delay requirements of applications and optimize system parameters. In the single receiver case, we demonstrate the trade-off between average packet delay, which we view as the inverse of throughput, and maximum ordered inter-arrival delay for various system parameters. For a single broadcast channel with multiple receivers having different delay constraints and feedback delays, we jointly optimize the coding parameters and time-division scheduling parameters at the transmitters. We formulate the optimization problem as a Generalized Geometric Program (GGP). This approach allows the transmitters to adjust adaptively the coding and scheduling parameters for efficient allocation of network resources under varying delay constraints. In the case where the receivers are served by multiple non-interfering wireless broadcast channels, the same optimization problem is formulated as a Signomial Program, which is NP-hard in general. We provide approximation methods using successive formulation of geometric programs and show the convergence of approximations.


STANSE: Bug-finding Framework for C Programs

Abstract: STANSE is a free (available under the GPLv2 license) modular framework for finding bugs in C programs using static analysis. Its two main design goals are 1) ability to process large software projects like the Linux kernel and 2) extensibility with new bug-finding techniques with a minimal effort. Currently there are four bug-finding algorithms implemented within STANSE: AutomatonChecker checks properties described in an automata-based formalism, ThreadChecker detects deadlocks among multiple threads, LockChecker finds locking errors based on statistics, and ReachabilityChecker looks for unreachable code. STANSE has been tested on the Linux kernel, where it has found dozens of previously undiscovered bugs.


Protection from Unresponsive Flows with Geometric CHOKe

Abstract: This paper proposes a simple and stateless active queue management (AQM) scheme, called geometric CHOKe (gCHOKe), to protect responsive flows from unresponsive ones. The proposed gCHOKe has its root on and is a generalization of the original CHOKe. It provides an extended power of flow protection, achieved by introducing an extra flow matching trial upon each successful matching of packets. Compared to the plain CHOKe, analysis and simulation show that gCHOKe can achieve over 20% improvement in the bounds of both bandwidth and buffer space used by an aggressive flow. In addition, up to 14% of the total link capacity can be saved from the unresponsive flow, allowing responsive or rate-adaptive flows to obtain a better share of resources in the router.


On the influence of intelligence in (social) intelligence testing environments

Abstract: This paper analyses the influence of including agents of different degrees of intelligence in a multiagent system. The goal is to better understand how we can develop intelligence tests that can evaluate social intelligence. We analyse several reinforcement algorithms in several contexts of cooperation and competition. Our experimental setting is inspired by the recently developed Darwin-Wallace distribution.


Graph sharing games: complexity and connectivity

Abstract: We study the following combinatorial game played by two players, Alice and Bob, which generalizes the Pizza game considered by Brown, Winkler and others. Given a connected graph G with nonnegative weights assigned to its vertices, the players alternately take one vertex of G in each turn. The first turn is Alice's. The vertices are to be taken according to one (or both) of the following two rules: (T) the subgraph of G induced by the taken vertices is connected during the whole game, (R) the subgraph of G induced by the remaining vertices is connected during the whole game. We show that if rules (T) and/or (R) are required then for every epsilon > 0 and for every positive integer k there is a k-connected graph G for which Bob has a strategy to obtain (1-epsilon) of the total weight of the vertices. This contrasts with the original Pizza game played on a cycle, where Alice is known to have a strategy to obtain 4/9 of the total weight. We show that the problem of deciding whether Alice has a winning strategy (i.e., a strategy to obtain more than half of the total weight) is PSPACE-complete if condition (R) or both conditions (T) and (R) are required. We also consider a game played on connected graphs (without weights) where the first player who violates condition (T) or (R) loses the game. We show that deciding who has the winning strategy is PSPACE-complete.


Practical Conditions for Well-behaved-ness of Anisotropic Voronoi Diagrams

Abstract: Recently, simple conditions for well-behaved-ness of anisotropic Voronoi diagrams have been proposed. While these conditions ensure well-behaved-ness of two types of practical anisotropic Voronoi diagrams, as well as the geodesic-distance one, in any dimension, they are both prohibitively expensive to evaluate, and not well-suited for typical problems in approximation or optimization. We propose simple conditions that can be efficiently evaluated, and are better suited to practical problems of approximation and optimization. The practical utility of this analysis is enhanced by the fact that orphan-free anisotropic Voronoi diagrams have embedded triangulations as duals.


Cyber-Insurance in Internet Security: A Dig into the Information Asymmetry Problem

Abstract: Internet users such as individuals and organizations are subject to different types of epidemic risks such as worms, viruses, spams, and botnets. To reduce the probability of risk, an Internet user generally invests in traditional security mechanisms like anti-virus and anti-spam software, sometimes also known as \emph{self-defense} mechanisms. However, according to security experts, such software (and their subsequent advancements) will not completely eliminate risk. Recent research efforts have considered the problem of residual risk elimination by proposing the idea of \emph{cyber-insurance}. In this regard, an important research problem is resolving information asymmetry issues associated with cyber-insurance contracts. In this paper we propose \emph{three} mechanisms to resolve information asymmetry in cyber-insurance. Our mechanisms are based on the \emph{Principal-Agent} (PA) model in microeconomic theory. We show that (1) optimal cyber-insurance contracts induced by our mechanisms only provide partial coverage to the insureds. This ensures greater self-defense efforts on the part of the latter to protect their computing systems, which in turn increases overall network security, (2) the level of deductible per network user contract increases in a concave manner with the topological degree of the user, and (3) a market for cyber-insurance can be made to exist in the presence of monopolistic insurers under effective mechanism design. Our methodology is applicable to any distributed network scenario in which a framework for cyber-insurance can be implemented.


The Impact of Secure OSs on Internet Security: What Cyber-Insurers Need to Know

Abstract: In recent years, researchers have proposed \emph{cyber-insurance} as a suitable risk-management technique for enhancing security in Internet-like distributed systems. However, amongst other factors, information asymmetry between the insurer and the insured, and the inter-dependent and correlated nature of cyber risks have contributed in a big way to the failure of cyber-insurance markets. Security experts have argued in favor of operating system (OS) platform switching (ex., from Windows to Unix-based OSs) or secure OS adoption as being one of the techniques that can potentially mitigate the problems posing a challenge to successful cyber-insurance markets. In this regard we model OS platform switching dynamics using a \emph{social gossip} mechanism and study three important questions related to the nature of the dynamics, for Internet-like distributed systems: (i) which type of networks should cyber-insurers target for insuring?, (ii) what are the bounds on the asymptotic performance level of a network, where the performance parameter is an average function of the long-run individual user willingness to adopt secure OSs?, and (iii) how can cyber-insurers use the topological information of their clients to incentivize/reward them during offering contracts? Our analysis is important to a profit-minded cyber-insurer, who wants to target the right network, design optimal contracts to resolve information asymmetry problems, and at the same time promote the increase of overall network security through increasing secure OS adoption amongst users.


The weighted words collector

Abstract: Motivated by applications in bioinformatics, we consider the word collector problem, i.e. the expected number of calls to a random weighted generator of words of length $n$ before the full collection is obtained. The originality of this instance of the non-uniform coupon collector lies in the, potentially large, multiplicity of the words/coupons of a given probability/composition. We obtain a general theorem that gives an asymptotic equivalent for the expected waiting time of a general version of the Coupon Collector. This theorem is especially well-suited for classes of coupons featuring high multiplicities. Its application to a given language essentially necessitates some knowledge on the number of words of a given composition/probability. We illustrate the application of our theorem, in a step-by-step fashion, on three exemplary languages, revealing asymptotic regimes in $\Theta(\mu(n)\cdot n)$ and $\Theta(\mu(n)\cdot \log n)$, where $\mu(n)$ is the sum of weights over words of length $n$.


Improving feature selection algorithms using normalised feature histograms

Abstract: The proposed feature selection method builds a histogram of the most stable features from random subsets of a training set and ranks the features based on a classifier based cross-validation. This approach reduces the instability of features obtained by conventional feature selection methods that occur with variation in training data and selection criteria. Classification results on four microarray and three image datasets using three major feature selection criteria and a naive Bayes classifier show considerable improvement over benchmark results.


Bundling Customers: How to Exploit Trust Among Customers to Maximize Seller Profit

Abstract: We consider an auction of identical digital goods to customers whose valuations are drawn independently from known distributions. Myerson's classic result identifies the truthful mechanism that maximizes the seller's expected profit. Under the assumption that in small groups customers can learn each others' valuations, we show how Myerson's result can be improved to yield a higher payoff to the seller using a mechanism that offers groups of customers to buy bundles of items.


{\pi}-Control: A Personal Cloud Control Centre

Abstract: Consumption of online services and cloud computing offerings is on the rise, largely due to compelling advantages over traditional local applications. From a user perspective, these include zero-maintenance of software, the always-on nature of such services, mashups of different applications and the networking effect with other users. Associated disadvantages are known, but effective means and tools to limit their effect are not yet well-established and not yet generally available to service users. We propose (1) a user-centric model of cloud elements beyond the conventional <SPI>aaS layers, including activities across trust zones, and (2) a personal control console for all individual and collaborative user activities in the cloud.


OWL: Yet to arrive on the Web of Data?

Abstract: Seven years on from OWL becoming a W3C recommendation, and two years on from the more recent OWL 2 W3C recommendation, OWL has still experienced only patchy uptake on the Web. Although certain OWL features (like owl:sameAs) are very popular, other features of OWL are largely neglected by publishers in the Linked Data world. This may suggest that despite the promise of easy implementations and the proposal of tractable profiles suggested in OWL's second version, there is still no "right" standard fragment for the Linked Data community. In this paper, we (1) analyse uptake of OWL on the Web of Data, (2) gain insights into the OWL fragment that is actually used/usable on the Web, where we arrive at the conclusion that this fragment is likely to be a simplified profile based on OWL RL, (3) propose and discuss such a new fragment, which we call OWL LD (for Linked Data).


Packing interval graphs with vertex-disjoint triangles

Abstract: We show that there exists a polynomial algorithm to pack interval graphs with vertex-disjoint triangles.


Considering a resource-light approach to learning verb valencies

Abstract: Here we describe work on learning the subcategories of verbs in a morphologically rich language using only minimal linguistic resources. Our goal is to learn verb subcategorizations for Quechua, an under-resourced morphologically rich language, from an unannotated corpus. We compare results from applying this approach to an unannotated Arabic corpus with those achieved by processing the same text in treebank form. The original plan was to use only a morphological analyzer and an unannotated corpus, but experiments suggest that this approach by itself will not be effective for learning the combinatorial potential of Arabic verbs in general. The lower bound on resources for acquiring this information is somewhat higher, apparently requiring a a part-of-speech tagger and chunker for most languages, and a morphological disambiguater for Arabic.


The Optimal Uncertainty Algorithm in the Mystic Framework

Abstract: We have recently proposed a rigorous framework for Uncertainty Quantification (UQ) in which UQ objectives and assumption/information set are brought into the forefront, providing a framework for the communication and comparison of UQ results. In particular, this framework does not implicitly impose inappropriate assumptions nor does it repudiate relevant information. This framework, which we call Optimal Uncertainty Quantification (OUQ), is based on the observation that given a set of assumptions and information, there exist bounds on uncertainties obtained as values of optimization problems and that these bounds are optimal. It provides a uniform environment for the optimal solution of the problems of validation, certification, experimental design, reduced order modeling, prediction, extrapolation, all under aleatoric and epistemic uncertainties. OUQ optimization problems are extremely large, and even though under general conditions they have finite-dimensional reductions, they must often be solved numerically. This general algorithmic framework for OUQ has been implemented in the mystic optimization framework. We describe this implementation, and demonstrate its use in the context of the Caltech surrogate model for hypervelocity impact.


Building a Framework for Predictive Science

Abstract: Key questions that scientists and engineers typically want to address can be formulated in terms of predictive science. Questions such as: "How well does my computational model represent reality?", "What are the most important parameters in the problem?", and "What is the best next experiment to perform?" are fundamental in solving scientific problems. Mystic is a framework for massively-parallel optimization and rigorous sensitivity analysis that enables these motivating questions to be addressed quantitatively as global optimization problems. Often realistic physics, engineering, and materials models may have hundreds of input parameters, hundreds of constraints, and may require execution times of seconds or longer. In more extreme cases, realistic models may be multi-scale, and require the use of high-performance computing clusters for their evaluation. Predictive calculations, formulated as a global optimization over a potential surface in design parameter space, may require an already prohibitively large simulation to be performed hundreds, if not thousands, of times. The need to prepare, schedule, and monitor thousands of model evaluations, and dynamically explore and analyze results, is a challenging problem that requires a software infrastructure capable of distributing and managing computations on large-scale heterogeneous resources. In this paper, we present the design behind an optimization framework, and also a framework for heterogeneous computing, that when utilized together, can make computationally intractable sensitivity and optimization problems much more tractable.


On Stability Problems of Omega and 3-Disjoint Paths Omega Multi-stage Interconnection Networks

Abstract: The research paper emphasizes that the Stable Matching problems are the same as the problems of stable configurations of Multi-stage Interconnection Networks (MIN). We have discusses the Stability Problems of Existing Regular Omega Multi-stage Interconnection Network (OMIN) and Proposed 3-Disjoint Paths Omega Multi-stage Interconnection Network (3DON) using the approaches and solutions provided by the Stable Matching Problem. Specifically, Stable Marriage Problem is used as an example of Stable Matching. On application of the concept of the Stable Marriage over the MINs states that OMIN is highly stable in comparison to 3DON.


The covert set-cover problem with application to Network Discovery

Abstract: We address a version of the set-cover problem where we do not know the sets initially (and hence referred to as covert) but we can query an element to find out which sets contain this element as well as query a set to know the elements. We want to find a small set-cover using a minimal number of such queries. We present a Monte Carlo randomized algorithm that approximates an optimal set-cover of size $OPT$ within $O(\log N)$ factor with high probability using $O(OPT \cdot \log^2 N)$ queries where $N$ is the input size. We apply this technique to the network discovery problem that involves certifying all the edges and non-edges of an unknown $n$-vertices graph based on layered-graph queries from a minimal number of vertices. By reducing it to the covert set-cover problem we present an $O(\log^2 n)$-competitive Monte Carlo randomized algorithm for the covert version of network discovery problem. The previously best known algorithm has a competitive ratio of $\Omega (\sqrt{n\log n})$ and therefore our result achieves an exponential improvement.


Towards 100 Gbps Ethernet: Development of Ethernet / Physical Layer Aspects

Abstract: Physical layer features of Ethernet from the first realization towards the 100 Gb Ethernet (100 GbE) development have been considered. Comparisons of these features are made according to the standardized data rates. Feasible physical layer options are then discussed for high data rates.


Regular Languages are Church-Rosser Congruential

Abstract: This paper proves a long standing conjecture in formal language theory. It shows that all regular languages are Church-Rosser congruential. The class of Church-Rosser congruential languages was introduced by McNaughton, Narendran, and Otto in 1988. A language L is Church-Rosser congruential, if there exists a finite confluent, and length-reducing semi-Thue system S such that L is a finite union of congruence classes modulo S. It was known that there are deterministic linear context-free languages which are not Church-Rosser congruential, but on the other hand it was strongly believed that all regular language are of this form. Actually, this paper proves a more general result.


Stone Age Distributed Computing

Abstract: The traditional models of distributed computing focus mainly on networks of computer-like devices that can exchange large messages with their neighbors and perform arbitrary local computations. Recently, there is a trend to apply distributed computing methods to networks of sub-microprocessor devices, e.g., biological cellular networks or networks of nano-devices. However, the suitability of the traditional distributed computing models to these types of networks is questionable: do tiny bio/nano nodes "compute" and/or "communicate" essentially the same as a computer? In this paper, we introduce a new model that depicts a network of randomized finite state machines operating in an asynchronous environment. Although the computation and communication capabilities of each individual device in the new model are, by design, much weaker than those of a computer, we show that some of the most important and extensively studied distributed computing problems can still be solved efficiently.


Topological approach to solve P versus NP

Abstract: This paper talks about difference between P and NP by using topological space that mean resolution principle. I pay attention to restrictions of antecedent and consequent in resolution, and show what kind of influence the restrictions have for difference of structure between P and NP regarding relations of relation. First, I show the restrictions of antecedent and consequent in resolution principle. Antecedents connect each other, and consequent become a linkage between these antecedents. And we can make consequent as antecedents product by using some resolutions which have same joint variable. We can determine these consequents reducible and irreducible. Second, I introduce RCNF that mean topology of resolution principle in CNF. RCNF is HornCNF and that variable values are presence of restrictions of CNF formula clauses. RCNF is P-Complete. Last, I introduce TCNF that have 3CNF's character which relate 2 variables relations with 1 variable. I show CNF complexity by using CCNF that combine some TCNF. TCNF is NP-Complete and product irreducible. I introduce CCNF that connect TCNF like Moore graph. We cannot reduce CCNF to RCNF with polynomial size. Therefore, TCNF is not in P.


Robust Multi-Robot Optimal Path Planning with Temporal Logic Constraints

Abstract: In this paper we present a method for automatically planning robust optimal paths for a group of robots that satisfy a common high level mission specification. Each robot's motion in the environment is modeled as a weighted transition system, and the mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied by the regions of the environment. In addition, an optimizing proposition must repeatedly be satisfied. The goal is to minimize the maximum time between satisfying instances of the optimizing proposition while ensuring that the LTL formula is satisfied even with uncertainty in the robots' traveling times. We characterize a class of LTL formulas that are robust to robot timing errors, for which we generate optimal paths if no timing errors are present, and we present bounds on the deviation from the optimal values in the presence of errors. We implement and experimentally evaluate our method considering a persistent monitoring task in a road network environment.


Asymptotically Optimal Algorithms for Pickup and Delivery Problems with Application to Large-Scale Transportation Systems

Abstract: The Stacker Crane Problem is NP-Hard and the best known approximation algorithm only provides a 9/5 approximation ratio. The objective of this paper is threefold. First, by embedding the problem within a stochastic framework, we present a novel algorithm for the SCP that: (i) is asymptotically optimal, i.e., it produces, almost surely, a solution approaching the optimal one as the number of pickups/deliveries goes to infinity; and (ii) has computational complexity $O(n^{2+\eps})$, where $n$ is the number of pickup/delivery pairs and $\eps$ is an arbitrarily small positive constant. Second, we asymptotically characterize the length of the optimal SCP tour. Finally, we study a dynamic version of the SCP, whereby pickup and delivery requests arrive according to a Poisson process, and which serves as a model for large-scale demand-responsive transport (DRT) systems. For such a dynamic counterpart of the SCP, we derive a necessary and sufficient condition for the existence of stable vehicle routing policies, which depends only on the workspace geometry, the stochastic distributions of pickup and delivery points, the arrival rate of requests, and the number of vehicles. Our results leverage a novel connection between the Euclidean Bipartite Matching Problem and the theory of random permutations, and, for the dynamic setting, exhibit novel features that are absent in traditional spatially-distributed queueing systems.


Contextual Bandit Learning with Predictable Rewards

Abstract: Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on the action and context. We consider this problem under a realizability assumption: there exists a function in a (known) function class, always capable of predicting the expected reward, given the action and context. Under this assumption, we show three things. We present a new algorithm---Regressor Elimination--- with a regret similar to the agnostic setting (i.e. in the absence of realizability assumption). We prove a new lower bound showing no algorithm can achieve superior performance in the worst case even with the realizability assumption. However, we do show that for any set of policies (mapping contexts to actions), there is a distribution over rewards (given context) such that our new algorithm has constant regret unlike the previous approaches.


Verifiable Computation with Massively Parallel Interactive Proofs

Abstract: As the cloud computing paradigm has gained prominence, the need for verifiable computation has grown increasingly urgent. The concept of verifiable computation enables a weak client to outsource difficult computations to a powerful, but untrusted, server. Protocols for verifiable computation aim to provide the client with a guarantee that the server performed the requested computations correctly, without requiring the client to perform the computations herself. By design, these protocols impose a minimal computational burden on the client. However, existing protocols require the server to perform a large amount of extra bookkeeping in order to enable a client to easily verify the results. Verifiable computation has thus remained a theoretical curiosity, and protocols for it have not been implemented in real cloud computing systems. Our goal is to leverage GPUs to reduce the server-side slowdown for verifiable computation. To this end, we identify abundant data parallelism in a state-of-the-art general-purpose protocol for verifiable computation, originally due to Goldwasser, Kalai, and Rothblum, and recently extended by Cormode, Mitzenmacher, and Thaler. We implement this protocol on the GPU, obtaining 40-120x server-side speedups relative to a state-of-the-art sequential implementation. For benchmark problems, our implementation reduces the slowdown of the server to factors of 100-500x relative to the original computations requested by the client. Furthermore, we reduce the already small runtime of the client by 100x. Similarly, we obtain 20-50x server-side and client-side speedups for related protocols targeted at specific streaming problems. We believe our results demonstrate the immediate practicality of using GPUs for verifiable computation, and more generally that protocols for verifiable computation have become sufficiently mature to deploy in real cloud computing systems.


Investigation to implicate data on clouds

Abstract: Cloud computing can and does mean different things to different people. The common characteristics most shares are on-demand secure access to metered services from nearly anywhere and dislocation of data from inside to outside the organization. Vision of cloud computing as a new IT procurement model. The system lifecycle, risks that are identified must be carefully balanced against the security and privacy controls available and the expected benefits from their utilization. Too many controls can be inefficient and ineffective, if the benefits outweigh the costs and associated risks. In this micro research, we characterize the problems related to security challenges.


Symbolic Models and Control of Discrete-Time Piecewise Affine Systems: An Approximate Simulation Approach

Abstract: Symbolic models have been recently used as a sound mathematical formalism for the formal verification and control design of purely continuous and hybrid systems. In this paper we propose a sequence of symbolic models that approximates a discrete-time Piecewise Affine (PWA) system in the sense of approximate simulation and converges to the PWA system in the so-called simulation metric. Symbolic control design is then addressed with specifications expressed in terms of non-deterministic finite automata. A sequence of symbolic control strategies is derived which converges, in the sense of simulation metric, to the maximal controller solving the given specification on the PWA system.


Modification of the Elite Ant System in Order to Avoid Local Optimum Points in the Traveling Salesman Problem

Abstract: This article presents a new algorithm which is a modified version of the elite ant system (EAS) algorithm. The new version utilizes an effective criterion for escaping from the local optimum points. In contrast to the classical EAC algorithms, the proposed algorithm uses only a global updating, which will increase pheromone on the edges of the best (i.e. the shortest) route and will at the same time decrease the amount of pheromone on the edges of the worst (i.e. the longest) route. In order to assess the efficiency of the new algorithm, some standard traveling salesman problems (TSPs) were studied and their results were compared with classical EAC and other well-known meta-heuristic algorithms. The results indicate that the proposed algorithm has been able to improve the efficiency of the algorithms in all instances and it is competitive with other algorithms.


Optimization in SMT with LA(Q) Cost Functions

Abstract: In the contexts of automated reasoning and formal verification, important decision problems are effectively encoded into Satisfiability Modulo Theories (SMT). In the last decade efficient SMT solvers have been developed for several theories of practical interest (e.g., linear arithmetic, arrays, bit-vectors). Surprisingly, very few work has been done to extend SMT to deal with optimization problems; in particular, we are not aware of any work on SMT solvers able to produce solutions which minimize cost functions over arithmetical variables. This is unfortunate, since some problems of interest require this functionality. In this paper we start filling this gap. We present and discuss two general procedures for leveraging SMT to handle the minimization of LA(Q) cost functions, combining SMT with standard minimization techniques. We have implemented the proposed approach within the MathSAT SMT solver. Due to the lack of competitors in AR and SMT domains, we experimentally evaluated our implementation against state-of-the-art tools for the domain of linear generalized disjunctive programming (LGDP), which is closest in spirit to our domain, on sets of problems which have been previously proposed as benchmarks for the latter tools. The results show that our tool is very competitive with, and often outperforms, these tools on these problems, clearly demonstrating the potential of the approach.


Fully Automatic Expression-Invariant Face Correspondence

Abstract: We consider the problem of computing accurate point-to-point correspondences among a set of human face scans with varying expressions. Our fully automatic approach does not require any manually placed markers on the scan. Instead, the approach learns the locations of a set of landmarks present in a database and uses this knowledge to automatically predict the locations of these landmarks on a newly available scan. The predicted landmarks are then used to compute point-to-point correspondences between a template model and the newly available scan. To accurately fit the expression of the template to the expression of the scan, we use as template a blendshape model. Our algorithm was tested on a database of human faces of different ethnic groups with strongly varying expressions. Experimental results show that the obtained point-to-point correspondence is both highly accurate and consistent for most of the tested 3D face models.


On the Transient Behavior of CHOKe

Abstract: CHOKe is a simple and stateless active queue management (AQM) scheme. Apart from low operational overhead, a highly attractive property of CHOKe is that it can protect responsive TCP flows from unresponsive UDP flows. Particularly, previous works have proven that CHOKe is able to bound both bandwidth share and buffer share of (a possible aggregate) UDP traffic (flow) on a link. However, these studies consider, and pertain only to, a steady state where the queue reaches equilibrium in the presence of many (long-lived) TCP flows and an unresponsive UDP flow of fixed arrival rate. If the steady state conditions are perturbed, particularly when UDP traffic rate changes over time, it is unclear whether the protection property of CHOKe still holds. Indeed, it can be examined, for example, that when UDP rate suddenly becomes 0 (i.e., flow stops), the unresponsive flow may assume close to full utilization in sub-RTT scales, potentially starving out the TCP flows. To explain this apparent discrepancy, this paper investigates CHOKe queue properties in a transient regime, which is the time period of transition between two steady states of the queue, initiated when the rate of the unresponsive flow changes. Explicit expressions that characterize flow throughputs in transient regimes are derived. These results provide additional understanding of CHOKe, and give some explanation on its intriguing behavior in the transient regime.


Content-aware Traffic Engineering

Abstract: Today, a large fraction of Internet traffic is originated by Content Providers (CPs) such as content distribution networks and hyper-giants. To cope with the increasing demand for content, CPs deploy massively distributed infrastructures. This poses new challenges for CPs as they have to dynamically map end-users to appropriate servers, without being fully aware of network conditions within an ISP as well as the end-users network locations. Furthermore, ISPs struggle to cope with rapid traffic shifts caused by the dynamic server selection process of CPs. In this paper, we argue that the challenges that CPs and ISPs face separately today can be turned into an opportunity. We show how they can jointly take advantage of the deployed distributed infrastructures to improve their operation and end-user performance. We propose Content-aware Traffic Engineering (CaTE), which dynamically adapts the traffic demand for content hosted on CPs by utilizing ISP network information and end-user location during the server selection process. As a result, CPs enhance their end-user to server mapping and improve end-user experience, thanks to the ability of network-informed server selection to circumvent network bottlenecks. In addition, ISPs gain the ability to partially influence the traffic demands in their networks. Our results with operational data show improvements in path length and delay between end-user and the assigned CP server, network wide traffic reduction of up to 15%, and a decrease in ISP link utilization of up to 40% when applying CaTE to traffic delivered by a small number of major CPs.


Send Mixed Signals -- Earn More, Work Less

Abstract: Emek et al. presented a model of probabilistic single-item second price auctions where an auctioneer who is informed about the type of an item for sale, broadcasts a signal about this type to uninformed bidders. They proved that finding the optimal (for the purpose of generating revenue) {\em pure} signaling scheme is strongly NP-hard. In contrast, we prove that finding the optimal {\em mixed} signaling scheme can be done in polynomial time using linear programming. For the proof, we show that the problem is strongly related to a problem of optimally bundling divisible goods for auctioning. We also prove that a mixed signaling scheme can in some cases generate twice as much revenue as the best pure signaling scheme and we prove a generally applicable lower bound on the revenue generated by the best mixed signaling scheme.


Singular Values using Cholesky Decomposition

Abstract: In this paper two ways to compute singular values are presented which use Cholesky decomposition as their basic operation.


Channel Estimation Study for Block - Pilot Insertion in OFDM Systems under Slowly Time Varying Conditions

Abstract: In this paper, we propose a study of performance of the channel estimation using LS, MMSE, LMMSE and Lr-LMMSE algorithms in OFDM (Orthogonal Frequency Division Multiplexing) system which, as known suffers from the time variation of the channel under high mobility conditions, using block pilot insertion. The loss of sub channel orthogonality leads to inter-carrier interference (ICI). Using many algorithms for channel estimation, we will show that, for a 16- QAM modulation, the LMMSE algorithm performs well to achieve this estimation but when the SNR (Signal Noise Rate) is high, the four algorithms (LS, MMSE, LMMSE and Lr-LMMSE) perform similarly, this is not always the case for another scheme of modulation. We will improve also the mean squared error for these algorithms. It will be illustrious in this paper that the LMMSE algorithm performs well with the block- pilot insertion as well as its low rank version which behave very good even when the size of FFT is very high.


On the Performance of Maximum Likelihood Inverse Reinforcement Learning

Abstract: Inverse reinforcement learning (IRL) addresses the problem of recovering a task description given a demonstration of the optimal policy used to solve such a task. The optimal policy is usually provided by an expert or teacher, making IRL specially suitable for the problem of apprenticeship learning. The task description is encoded in the form of a reward function of a Markov decision process (MDP). Several algorithms have been proposed to find the reward function corresponding to a set of demonstrations. One of the algorithms that has provided best results in different applications is a gradient method to optimize a policy squared error criterion. On a parallel line of research, other authors have presented recently a gradient approximation of the maximum likelihood estimate of the reward signal. In general, both approaches approximate the gradient estimate and the criteria at different stages to make the algorithm tractable and efficient. In this work, we provide a detailed description of the different methods to highlight differences in terms of reward estimation, policy similarity and computational costs. We also provide experimental results to evaluate the differences in performance of the methods.


Efficient Query Verification on Outsourced Data: A Game-Theoretic Approach

Abstract: To save time and money, businesses and individuals have begun outsourcing their data and computations to cloud computing services. These entities would, however, like to ensure that the queries they request from the cloud services are being computed correctly. In this paper, we use the principles of economics and competition to vastly reduce the complexity of query verification on outsourced data. We consider two cases: First, we consider the scenario where multiple non-colluding data outsourcing services exist, and then we consider the case where only a single outsourcing service exists. Using a game theoretic model, we show that given the proper incentive structure, we can effectively deter dishonest behavior on the part of the data outsourcing services with very few computational and monetary resources. We prove that the incentive for an outsourcing service to cheat can be reduced to zero. Finally, we show that a simple verification method can achieve this reduction through extensive experimental evaluation.


Beyond Sentiment: The Manifold of Human Emotions

Abstract: Sentiment analysis predicts the presence of positive or negative emotions in a text document. In this paper we consider higher dimensional extensions of the sentiment concept, which represent a richer set of human emotions. Our approach goes beyond previous work in that our model contains a continuous manifold rather than a finite set of human emotions. We investigate the resulting model, compare it to psychological observations, and explore its predictive capabilities. Besides obtaining significant improvements over a baseline without manifold, we are also able to visualize different notions of positive sentiment in different domains.


MEGCOM: Min-Energy Group COMmunication in Multi-hop Wireless Networks

Abstract: Given the increasing demand from wireless applications, designing energy-efficient group communication protocols is of great importance to multi-hop wireless networks. A group communication session involves a set of member nodes, each of them needs to send a certain number of data packets to all other members. In this paper, we consider the problem of building a shared multicast tree spanning the member nodes such that the total energy consumption of a group communication session using the shared multicast tree is minimized. Since this problem was proven as NP-complete, we propose, under our Min-Energy Group COMmunication (MEGCOM) framework, three distributed approximation algorithms with provable approximation ratios. When the transmission power of each wireless node is fixed, our first two algorithms have the approximation ratios of O(ln(\Delta+ 1)) and O(1), respectively, where \Delta is the maximum node degree in the network. When the transmission power of each wireless node is adjustable, our third algorithm again delivers a constant approximation ratio. We also use extensive simulations to verify the practical performance of our algorithms.


Robust seed selection algorithm for k-means type algorithms

Abstract: Selection of initial seeds greatly affects the quality of the clusters and in k-means type algorithms. Most of the seed selection methods result different results in different independent runs. We propose a single, optimal, outlier insensitive seed selection algorithm for k-means type algorithms as extension to k-means++. The experimental results on synthetic, real and on microarray data sets demonstrated that effectiveness of the new algorithm in producing the clustering results


Automatic Clustering with Single Optimal Solution

Abstract: Determining optimal number of clusters in a dataset is a challenging task. Though some methods are available, there is no algorithm that produces unique clustering solution. The paper proposes an Automatic Merging for Single Optimal Solution (AMSOS) which aims to generate unique and nearly optimal clusters for the given datasets automatically. The AMSOS is iteratively merges the closest clusters automatically by validating with cluster validity measure to find single and nearly optimal clusters for the given data set. Experiments on both synthetic and real data have proved that the proposed algorithm finds single and nearly optimal clustering structure in terms of number of clusters, compactness and separation.


Signaling Schemes for Revenue Maximization

Abstract: Signaling is an important topic in the study of asymmetric information in economic settings. In particular, the transparency of information available to a seller in an auction setting is a question of major interest. We introduce the study of signaling when conducting a second price auction of a probabilistic good whose actual instantiation is known to the auctioneer but not to the bidders. This framework can be used to model impressions selling in display advertising. We study the problem of computing a signaling scheme that maximizes the auctioneer's revenue in a Bayesian setting. While the general case is proved to be computationally hard, several cases of interest are shown to be polynomially solvable. In addition, we establish a tight bound on the minimum number of signals required to implement an optimal signaling scheme and show that at least half of the maximum social welfare can be preserved within such a scheme.


On the Invariance of the Unitary Cost Model for Head Reduction (Long Version)

Abstract: The lambda calculus is a widely accepted computational model of higher-order functional pro- grams, yet there is not any direct and universally accepted cost model for it. As a consequence, the computational difficulty of reducing lambda terms to their normal form is typically studied by reasoning on concrete implementation algorithms. In this paper, we show that when head reduction is the underlying dynamics, the unitary cost model is indeed invariant. This improves on known results, which only deal with weak (call-by-value or call-by-name) reduction. Invariance is proved by way of a linear calculus of explicit substitutions, which allows to nicely decompose any head reduction step in the lambda calculus into more elementary substitution steps, thus making the combinatorics of head-reduction easier to reason about. The technique is also a promising tool to attack what we see as the main open problem, namely understanding for which normalizing strategies derivation complexity is an invariant cost model, if any.


Open Data: Reverse Engineering and Maintenance Perspective

Abstract: Open data is an emerging paradigm to share large and diverse datasets -- primarily from governmental agencies, but also from other organizations -- with the goal to enable the exploitation of the data for societal, academic, and commercial gains. There are now already many datasets available with diverse characteristics in terms of size, encoding and structure. These datasets are often created and maintained in an ad-hoc manner. Thus, open data poses many challenges and there is a need for effective tools and techniques to manage and maintain it. In this paper we argue that software maintenance and reverse engineering have an opportunity to contribute to open data and to shape its future development. From the perspective of reverse engineering research, open data is a new artifact that serves as input for reverse engineering techniques and processes. Specific challenges of open data are document scraping, image processing, and structure/schema recognition. From the perspective of maintenance research, maintenance has to accommodate changes of open data sources by third-party providers, traceability of data transformation pipelines, and quality assurance of data and transformations. We believe that the increasing importance of open data and the research challenges that it brings with it may possibly lead to the emergence of new research streams for reverse engineering as well as for maintenance.


Signcryption scheme based on schnorr digital signature

Abstract: This article presents a new signcryption scheme which is based on the Schnorr digital signature algorithm. The new scheme represents my personal contribution to signcryption area. I have been implemented the algorithm in a program and here are provided the steps of the algorithm, the results and some examples. The paper also contains the presentation of the original Signcryption scheme, based on ElGamal digital signature and discusses the practical applications of Signcryption in real life.


Trust Based Scheme for QoS Assurance in Mobile Ad-Hoc Networks

Abstract: A mobile ad-hoc network (MANET) is a peer-to-peer wireless network where nodes can communicate with each other without the use of infrastructure such as access points or base stations. These networks are self-configuring, capable of self-directed operation and hastily deployable. Nodes cooperate to provide connectivity, operates without centralized administration. Nodes are itinerant, topology can be very dynamic and nodes must be able to relay traffic since communicating nodes might be out of range. The dynamic nature of MANET makes network open to attacks and unreliability. Routing is always the most significant part for any networks. Each node should not only work for itself, but should be cooperative with other nodes. Node misbehaviour due to selfish or malicious intention could significantly degrade the performance of MANET. The Qos parameters like PDR, throughput and delay are affected directly due to such misbehaving nodes. We focus on trust management framework, which is intended to cope with misbehaviour problem of node and increase the performance of MANETs. A trust-based system can be used to track this misbehaving of nodes, spot them and isolate them from routing and provide reliability. In this paper a Trust Based Reliable AODV [TBRAODV] protocol is presented which implements a trust value for each node. For every node trust value is calculated and based trust value nodes are allowed to participate in routing or else identified to become a misbehaving node. This enhances reliability in AODV routing and results in increase of PDR, decrease in delay and throughput is maintained. This work is implemented and simulated on NS-2. Based on simulation results, the proposed protocol provides more consistent and reliable data transfer compared with general AODV, if there are misbehaving nodes in the MANET


The impact of propagation environment and traffic load on the performance of routing protocols in ad hoc networks

Abstract: Wireless networks are characterized by a dynamic topology triggered by the nodes mobility. Thus, the wireless multi-hops connection and the channel do not have a determinist behaviour such as: interference or multiple paths. Moreover, the nodes' invisibility makes the wireless channel difficult to detect. This wireless networks' behaviour should be scrutinized. In our study, we mainly focus on radio propagation models by observing the evolution of the routing layer's performances in terms of the characteristics of the physical layer. For this purpose, we first examine and then display the simulation findings of the impact of different radio propagation models on the performance of ad hoc networks. To fully understand how these various radio models influence the networks performance, we have compared the performances of several routing protocols (DSR, AODV, and DSDV) for each propagation model. To complete our study, a comparison of energy performance based routing protocols and propagation models are presented. In order to reach credible results, we focused on the notion of nodes' speed and the number of connections by using the well known network simulator NS-2.


Design of wireless electronic stethoscope based on zigbee

Abstract: Heart sound stethoscope is primary stage to access diseases. In this paper design of an electronic stethoscope with the functions of wireless transmission is discussed. This electronic stethoscope based on embedded processor. The data can be transmitted through wireless transmission using Zigbee module. A microphone is used to pick up the sound of the heart beat. Acoustic stethoscope can be changed into a digital stethoscope by inserting an electric capacity microphone into its head. The signal is processed and amplified to play with or without earphone. Heart sounds are processed, sampled and sent wirelessly using Zigbee module so that multiple doctors can do auscultation. PC connectivity is provided through serial port where from audio and video can be made available through LAN and internet for telemedicine consultation. Heart beat signals are sensed, sent, displayed, monitored, stored, reviewed, and analysed with ease.


Deployment of mobile routers ensuring coverage and connectivity

Abstract: Maintaining connectivity among a group of autonomous agents exploring an area is very important, as it promotes cooperation between the agents and also helps message exchanges which are very critical for their mission. Creating an underlying Ad-hoc Mobile Router Network (AMRoNet) using simple robotic routers is an approach that facilitates communication between the agents without restricting their movements. We address the following question in our paper: How to create an AMRoNet with local information and with minimum number of routers? We propose two new localized and distributed algorithms 1) agent-assisted router deployment and 2) a self-spreading for creating AMRoNet. The algorithms use a greedy deployment strategy for deploying routers effectively into the area maximizing coverage and a triangular deployment strategy to connect different connected component of routers from different base stations. Empirical analysis shows that the proposed algorithms are the two best localized approaches to create AMRoNets.


Combined Haar-Hilbert and Log-Gabor Based Iris Encoders

Abstract: This chapter shows that combining Haar-Hilbert and Log-Gabor improves iris recognition performance leading to a less ambiguous biometric decision landscape in which the overlap between the experimental intra- and interclass score distributions diminishes or even vanishes. Haar-Hilbert, Log-Gabor and combined Haar-Hilbert and Log-Gabor encoders are tested here both for single and dual iris approach. The experimental results confirm that the best performance is obtained for the dual iris approach when the iris code is generated using the combined Haar-Hilbert and Log-Gabor encoder, and when the matching score fuses the information from both Haar-Hilbert and Log-Gabor channels of the combined encoder.


User profile based proportional share scheduling and mac protocol for manets

Abstract: Quality of Service(QoS) in Mobile Ad Hoc Networks (MANETs) though a challenge, becomes a necessity because of its applications in critical scenarios. Providing QoS for users belonging to various profiles and playing different roles, becomes the need of the hour. In this paper, we propose proportional share scheduling and MAC protocol (PS2-MAC) model. It classifies users based on their profile as High Profiled users (HP), Medium Profiled users (MP) and Low profiled users (LP) and assigns proportional weights. Service Differentiation for these three service classes is achieved through, rationed dequeuing algorithm, variable inter frame space, proportionate prioritized backoff timers and enhanced RTS/CTS control packets. Differentiated services is simulated in ns2 and results show that 9.5% control overhead is reduced in our proposed scheme than the existing scheme and results also justify that, differentiated services have been achieved for the different profiles of users with proportionate shares and thereby reducing starvation.


Learning to Place New Objects in a Scene

Abstract: Placing is a necessary skill for a personal robot to have in order to perform tasks such as arranging objects in a disorganized room. The object placements should not only be stable but also be in their semantically preferred placing areas and orientations. This is challenging because an environment can have a large variety of objects and placing areas that may not have been seen by the robot before. In this paper, we propose a learning approach for placing multiple objects in different placing areas in a scene. Given point-clouds of the objects and the scene, we design appropriate features and use a graphical model to encode various properties, such as the stacking of objects, stability, object-area relationship and common placing constraints. The inference in our model is an integer linear program, which we solve efficiently via an LP relaxation. We extensively evaluate our approach on 98 objects from 16 categories being placed into 40 areas. Our robotic experiments show a success rate of 98% in placing known objects and 82% in placing new objects stably. We use our method on our robots for performing tasks such as loading several dish-racks, a bookshelf and a fridge with multiple items.


A Polynomial Time Approximation Scheme for a Single Machine Scheduling Problem Using a Hybrid Evolutionary Algorithm

Abstract: Nowadays hybrid evolutionary algorithms, i.e, heuristic search algorithms combining several mutation operators some of which are meant to implement stochastically a well known technique designed for the specific problem in question while some others playing the role of random search, have become rather popular for tackling various NP-hard optimization problems. While empirical studies demonstrate that hybrid evolutionary algorithms are frequently successful at finding solutions having fitness sufficiently close to the optimal, many fewer articles address the computational complexity in a mathematically rigorous fashion. This paper is devoted to a mathematically motivated design and analysis of a parameterized family of evolutionary algorithms which provides a polynomial time approximation scheme for one of the well-known NP-hard combinatorial optimization problems, namely the "single machine scheduling problem without precedence constraints". The authors hope that the techniques and ideas developed in this article may be applied in many other situations.


A family of weakly universal cellular automata in the hyperbolic plane with two states

Abstract: In this paper, we construct a family of weakly universal rotation invariant cellular automaton for all grids $\{p,3\}$ of the hyperbolic plane for $p\geq 13$. The scheme is general for $p\geq 17$ and for $13\leq p<17$, we give such a cellular automaton for $p=13$, which is enough. Also, an important property of this family is that the set of cells of the cellular automaton which are subject to changes is actually a planar set. The problem for $p<13$ for a truly planar construction is still open. The best result, for $p=7$, is four states and was obtained by the same author.


Multi-outcome and Multidimensional Market Scoring Rules

Abstract: Hanson's market scoring rules allow us to design a prediction market that still gives useful information even if we have an illiquid market with a limited number of budget-constrained agents. Each agent can "move" the current price of a market towards their prediction. While this movement still occurs in multi-outcome or multidimensional markets we show that no market-scoring rule, under reasonable conditions, always moves the price directly towards beliefs of the agents. We present a modified version of a market scoring rule for budget-limited traders, and show that it does have the property that, from any starting position, optimal trade by a budget-limited trader will result in the market being moved towards the trader's true belief. This mechanism also retains several attractive strategic properties of the market scoring rule.


Improve the Practice of Software Development in India by Having a Software Development Career Track in Indian CS & IT Academia

Abstract: Many, but not all, Indian CS & IT academics tend to have a focus on theory and research. They do not give much importance to the practice of software development. This paper proposes an additional software development career track for Indian CS & IT academics different from the existing research oriented career track. A measure of software contribution record is suggested. It opines that adoption of such changes to academic regulations will result in significant improvement of software development skill set in Indian CS & IT academia which, in turn, will result in better software development skill set in Indian CS & IT graduates.


Collaboration for enhancing the system development process in open source diligence

Abstract: According to different opponents and commercial giants in software industries, the open source style software development has enough capacity to complete successfully the large scale projects. But we have seen many flaws and loops in collaboration and handling of mega scale projects in open source environment. Perhaps the collaboration is a key of successful project development. In this article we have tries to identify different feasible and reliable solution to a better collaboration ways in the open source system development. Some of the issues also that are found in the development phase of the open source have been identified and a proposed solution by explaining Successful communities such as GNU, the Apache Software Foundation, and Eclipse Foundation is discusses in this research article. It must be kept in mind that to improvement the collaboration in open source environment both the development community and the people should be more creative.


A transformation approach for collaboration based requirement models

Abstract: Distributed software engineering is widely recognized as a complex task. Among the inherent complexities is the process of obtaining a system design from its global requirement specification. This paper deals with such transformation process and suggests an approach to derive the behavior of a given system components, in the form of distributed Finite State Machines, from the global system requirements, in the form of an augmented UML Activity Diagrams notation. The process of the suggested approach is summarized in three steps: the definition of the appropriate source Meta-Model (requirements Meta-Model), the definition of the target Design Meta-Model and the definition of the rules to govern the transformation during the derivation process. The derivation process transforms the global system requirements described as UML diagram activities (extended with collaborations) to system roles behaviors represented as UML finite state machines. The approach is implemented using Atlas Transformation Language (ATL).


Performance evaluation aodv, dymo, olsr and zrpad hoc routing protocol for ieee 802.11 mac and 802.11 dcf in vanet using qualnet

Abstract: In VANET high speed is the real characteristics which leads to frequent breakdown, interference etc. Therefore Performance of adhoc routing protocols is helpful to improve the Quality of Service (QOS). In this paper we studied various adhoc routing protocols, Reactive, Proactive & Hybrid, taking in to consideration parameters like speed, altitude, mobility etc in real VANET scenario. The AODV and DYMO (Reactive), OLSR (Proactive) and ZRP (hybrid) protocols are compared for IEEE 802.11(MAC) and IEEE 802.11(DCF) standard using Qualnet as a Simulation tool. Since IEEE 802.11, covers both physical and data link layer. Hence performance of the protocols in these layers helps to make a right selection of Protocol for high speed mobility. Varying parameters of VANET shows that in the real traffic scenarios proactive protocol performs more efficiently for IEEE 802.11 (MAC) and IEEE 802.11(DCF).


Handover Necessity Estimation for 4G Heterogeneous Networks

Abstract: One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively.


Stabilizing sliding mode control design and application for a dc motor: Speed control

Abstract: The regulation by sliding mode control (SMC) is recognized for its qualities of robustness and dynamic response. This article will briefly talk about the regulation principles by sliding mode as well as the application of this approach to the adjustment of a speed control DC motor bench using the TY36A/EV unit. This unit, from Electronica Veneta products, uses a PID controller to control the speed and position of the DC motor. Our purpose is to improve the set time answer and the robustness of the system when disturbances take place. The experimental results show very good performances of the proposed approach relatively to the PID.


Review of syn-flooding attack detection mechanism

Abstract: Denial of Service (DoS) is a security threat which compromises the confidentiality of information stored in Local Area Networks (LANs) due to unauthorized access by spoofed IP addresses. SYN Flooding is a type of DoS which is harmful to network as the flooding of packets may delay other users from accessing the server and in severe cases, the server may need to be shut down, wasting valuable resources, especially in critical real-time services such as in e-commerce and the medical field. The objective of this paper is to review the state-of-the art of detection mechanisms for SYN flooding. The detection schemes for SYN Flooding attacks have been classified broadly into three categories - detection schemes based on the router data structure, detection schemes based on statistical analysis of the packet flow and detection schemes based on artificial intelligence. The advantages and disadvantages for various detection schemes under each category have been critically examined. The performance measures of the categories have also been compared.


Personalised product design using virtual interactive techniques

Abstract: Use of Virtual Interactive Techniques for personalized product design is described in this paper. Usually products are designed and built by considering general usage patterns and Prototyping is used to mimic the static or working behaviour of an actual product before manufacturing the product. The user does not have any control on the design of the product. Personalized design postpones design to a later stage. It allows for personalized selection of individual components by the user. This is implemented by displaying the individual components over a physical model constructed using Cardboard or Thermocol in the actual size and shape of the original product. The components of the equipment or product such as screen, buttons etc. are then projected using a projector connected to the computer into the physical model. Users can interact with the prototype like the original working equipment and they can select, shape, position the individual components displayed on the interaction panel using simple hand gestures. Computer Vision techniques as well as sound processing techniques are used to detect and recognize the user gestures captured using a web camera and microphone.


A Proposed Architecture for Continuous Web Monitoring Through Online Crawling of Blogs

Abstract: Getting informed of what is registered in the Web space on time, can greatly help the psychologists, marketers and political analysts to familiarize, analyse, make decision and act correctly based on the society`s different needs. The great volume of information in the Web space hinders us to continuously online investigate the whole space of the Web. Focusing on the considered blogs limits our working domain and makes the online crawling in the Web space possible. In this article, an architecture is offered which continuously online crawls the related blogs, using focused crawler, and investigates and analyses the obtained data. The online fetching is done based on the latest announcements of the ping server machines. A weighted graph is formed based on targeting the important key phrases, so that a focused crawler can do the fetching of the complete texts of the related Web pages, based on the weighted graph.


Semantic Visualization and Navigation in Textual Corpus

Abstract: This paper gives a survey of related work on the information visualization domain and study the real integration of the cartography paradigms in actual information search systems. Based on this study, we propose a semantic visualization and navigation approach which offer to users three search modes: precise search, connotative search and thematic search. The objective is to propose to the users of an information search system, new interaction paradigms which support the semantic aspect of the considered information space and guide users in their searches by assisting them to locate their interest center and to improve serendipity.


Network Backbone Discovery Using Edge Clustering

Abstract: In this paper, we investigate the problem of network backbone discovery. In complex systems, a "backbone" takes a central role in carrying out the system functionality and carries the bulk of system traffic. It also both simplifies and highlight underlying networking structure. Here, we propose an integrated graph theoretical and information theoretical network backbone model. We develop an efficient mining algorithm based on Kullback-Leibler divergence optimization procedure and maximal weight connected subgraph discovery procedure. A detailed experimental evaluation demonstrates both the effectiveness and efficiency of our approach. The case studies in the real world domain further illustrates the usefulness of the discovered network backbones.


Principle of Virtual Use Method in Common Gateway Interface Program on the DACS Scheme

Abstract: In the world of the Internet, Web Servers such as Apache and Internet Information Server (IIS) were developed to exchange information among client computers having different Operation System. They have only the function of displaying static information such as HTML files and image files into the Web Browser. However, when the information is updated, the administrator updates it by manual operation. In some cases, because it is necessary to update several places about the same information, the work load becomes high than it is assume and update error and update omission may occur. These problems were solved by use of a Common Gateway Interface (CGI) program such as a bulletin board system and a Blog system. However, these programs opened to Internet have often no user authentication mechanism and no access control mechanism. That is, they have the problem that user can access it freely only by getting the URL and inputting it to a Web Browser. Therefore, in this paper, we show a method to add the user authentication and access control mechanism for them. It is called virtual use method of CGI and is realized in the case of introducing the Destination Addressing Control System (DACS) Scheme, which is a kind of Policy Based Network Management Scheme (PBNM). As the result, this kind of the CGI program can be used in the organization with the above two functions.


Effect of Packet Delay Variation on Video-Voice over DiffServ-MPLS in IPv4-IPv6 Networks

Abstract: Over the last years, we have witnessed a rapid deployment of real-time applications on the Internet as well as many research works about Quality of Service (QoS), in particular IPv4 (Internet Protocol version 4). The inevitable exhaustion of the remaining IPv4 address pool has become progressively evident. As the evolution of Internet Protocol (IP) continues, the deployment of IPv6 QoS is underway. Today, there is limited experience in the deployment of QoS for IPv6 traffic in MPLS backbone networks in conjunction with DiffServ (Differentiated Services) support. DiffServ itself does not have the ability to control the traffic which has been taken for end-to-end path while a number of links of the path are congested. In contrast, MPLS Traffic Engineering (TE) is accomplished to control the traffic and can set up end-to-end routing path before data has been forwarded. From the evolution of IPv4 QoS solutions, we know that the integration of DiffServ and MPLS TE satisfies the guaranteed QoS requirement for real-time applications. This paper presents a QoS performance study of real-time applications such as voice and video conferencing in terms of Packet Delay Variation (PDV) over DiffServ with or without MPLS TE in IPv4/IPv6 networks using Optimized Network Engineering Tool (OPNET). We also study the interaction of Expedited Forwarding (EF), Assured Forwarding (AF) traffic aggregation, link congestion, as well as the effect of performance metric such as PDV. The effectiveness of DiffServ and MPLS TE integration in IPv4/IPv6 network is illustrated and analyzed. This paper shows that IPv6 experiences more PDV than their IPv4 counterparts.


A personalized web page content filtering model based on segmentation

Abstract: In the view of massive content explosion in World Wide Web through diverse sources, it has become mandatory to have content filtering tools. The filtering of contents of the web pages holds greater significance in cases of access by minor-age people. The traditional web page blocking systems goes by the Boolean methodology of either displaying the full page or blocking it completely. With the increased dynamism in the web pages, it has become a common phenomenon that different portions of the web page holds different types of content at different time instances. This paper proposes a model to block the contents at a fine-grained level i.e. instead of completely blocking the page it would be efficient to block only those segments which holds the contents to be blocked. The advantages of this method over the traditional methods are fine-graining level of blocking and automatic identification of portions of the page to be blocked. The experiments conducted on the proposed model indicate 88% of accuracy in filtering out the segments.


Classification of artificial intelligence ids for smurf attack

Abstract: Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf attack with much reliable accuracy.


Hyper heuristic based on great deluge and its variants for exam timetabling problem

Abstract: Today, University Timetabling problems are occurred annually and they are often hard and time consuming to solve. This paper describes Hyper Heuristics (HH) method based on Great Deluge (GD) and its variants for solving large, highly constrained timetabling problems from different domains. Generally, in hyper heuristic framework, there are two main stages: heuristic selection and move acceptance. This paper emphasizes on the latter stage to develop Hyper Heuristic (HH) framework. The main contribution of this paper is that Great Deluge (GD) and its variants: Flex Deluge(FD), Non-linear(NLGD), Extended Great Deluge(EGD) are used as move acceptance method in HH by combining Reinforcement learning (RL).These HH methods are tested on exam benchmark timetabling problem and best results and comparison analysis are reported.


Improving energy efficiency in wireless sensor networks through scheduling and routing

Abstract: This paper is about the wireless sensor network in environmental monitoring applications. A Wireless Sensor Network consists of many sensor nodes and a base station. The number and type of sensor nodes and the design protocols for any wireless sensor network is application specific. The sensor data in this application may be light intensity, temperature, pressure, humidity and their variations .Clustering and routing are the two areas which are given more attention in this paper.


Encryption of Data using Elliptic Curve over Finite fields

Abstract: Cryptography is the study of techniques for ensuring the secrecy and authentication of the information. Public-key encryption schemes are secure only if the authenticity of the public-key is assured. Elliptic curve arithmetic can be used to develop a variety of elliptic curve cryptography (ECC) schemes including key exchange, encryption and digital signature. The principal attraction of elliptic curve cryptography compared to RSA is that it offers equal security for a smaller key-size, thereby reducing the processing overhead. In the present paper we propose a new encryption algorithm using some Elliptic Curve over finite fields


The black-and-white coloring problem on circle graphs

Abstract: Given a graph G and integers b and w. The black-and-white coloring problem asks if there exist disjoint sets of vertices B and W with |B|=b and |W|=w such that no two vertices x in B and y in W are adjacent. In this paper we show that the problem is polynomial when restricted to permutation graphs and, more generally, to circle graphs.


A Block Cipher using Rotation and Logical XOR Operations

Abstract: Cryptography is the study of methods of sending messages in disguised form so that only the intended recipients can remove the disguise and read the messages. Information security has become a very critical aspect of modern communication systems. With the global acceptance of the Internet as a medium of communication, virtually every computer in the world is connected to every other. It has created a new risk for the users of the computers with a constant threat of being hacked and being victims of data theft. In this connection data encryption has become an essential part of secure communication of the messages. In the present paper we propose a new method of encryption of data in blocks using the operations Rotation and Logical XOR


Global Maps of Science based on the new Web-of-Science Categories

Abstract: In August 2011, Thomson Reuters launched version 5 of the Science and Social Science Citation Index in the Web of Science (WoS). Among other things, the 222 ISI Subject Categories (SCs) for these two databases in version 4 of WoS were renamed and extended to 225 WoS Categories (WCs). A new set of 151 Subject Categories (SCs) was added, but at a higher level of aggregation. Since we previously used the ISI SCs as the baseline for a global map in Pajek (Rafols et al., 2010) and brought this facility online (at http://www.leydesdorff.net/overlaytoolkit), we recalibrated this map for the new WC categories using the Journal Citation Reports 2010. In the new installation, the base maps can also be made using VOSviewer (Van Eck & Waltman, 2010).


A Reliable Semi-Distributed Load Balancing Architecture of Heterogeneous Wireless Networks

Abstract: Now a day's Heterogeneous wireless network is a promising field of research interest. Various challenges exist in this hybrid combination like load balancing, resource management and so on. In this paper we introduce a reliable load balancing architecture for heterogeneous wireless communications to ensure certain level of quality of service. To conquer the problem of centralized and distributed design, a semi distributed load balancing architecture for multiple access networks is introduced. In this grid based design multiple Load and Mobile Agent Management Units is incorporated. To prove the compactness of the design, integrated reliability, signalling overhead and total processing time is calculated. And finally simulation result shows that overall system performance is improved by enhancing reliability, reducing signalling overhead and processing time.


FATAL+: A Self-Stabilizing Byzantine Fault-tolerant Clocking Scheme for SoCs

Abstract: We present concept and implementation of a self-stabilizing Byzantine fault-tolerant distributed clock generation scheme for multi-synchronous GALS architectures in critical applications. It combines a variant of a recently introduced self-stabilizing algorithm for generating low-frequency, low-accuracy synchronized pulses with a simple non-stabilizing high-frequency, high-accuracy clock synchronization algorithm. We provide thorough correctness proofs and a performance analysis, which use methods from fault-tolerant distributed computing research but also addresses hardware-related issues like metastability. The algorithm, which consists of several concurrent communicating asynchronous state machines, has been implemented in VHDL using Petrify in conjunction with some extensions, and synthetisized for an Altera Cyclone FPGA. An experimental validation of this prototype has been carried out to confirm the skew and clock frequency bounds predicted by the theoretical analysis, as well as the very short stabilization times (required for recovering after excessively many transient failures) achievable in practice.


Smoothed Complexity Theory

Abstract: Smoothed analysis is a new way of analyzing algorithms introduced by Spielman and Teng (J. ACM, 2004). Classical methods like worst-case or average-case analysis have accompanying complexity classes, like P and AvgP, respectively. While worst-case or average-case analysis give us a means to talk about the running time of a particular algorithm, complexity classes allows us to talk about the inherent difficulty of problems. Smoothed analysis is a hybrid of worst-case and average-case analysis and compensates some of their drawbacks. Despite its success for the analysis of single algorithms and problems, there is no embedding of smoothed analysis into computational complexity theory, which is necessary to classify problems according to their intrinsic difficulty. We propose a framework for smoothed complexity theory, define the relevant classes, and prove some first hardness results (of bounded halting and tiling) and tractability results (binary optimization problems, graph coloring, satisfiability). Furthermore, we discuss extensions and shortcomings of our model and relate it to semi-random models.


An Intelligent Mobile-Agent Based Scalable Network Management Architecture for Large-Scale Enterprise System

Abstract: Several Mobile Agent based distributed network management models have been proposed in recent times to address the scalability and flexibility problems of centralized (SNMP or CMIP management models) models. Though the use of Mobile Agents to distribute and delegate management tasks comes handy in dealing with the previously stated issues, many of the agent-based management frameworks like initial flat bed models and static mid-level managers employing mobile agents models cannot efficiently meet the demands of current networks which are growing in size and complexity. Moreover, varied technologies, such as SONET, ATM, Ethernet, DWDM etc., present at different layers of the Access, Metro and Core (long haul) sections of the network, have contributed to the complexity in terms of their own framing and protocol structures. Thus, controlling and managing the traffic in these networks is a challenging task. This paper presents an intelligent scalable hierarchical agent based model for the management of large-scale complex networks to address aforesaid issues. The cost estimation, carried out with a view to compute the overall management cost in terms of management data overhead, is being presented. The results obtained thereafter establish the usefulness of the presented architecture as compare to centralized and flat bed agent based models.


3D Model Assisted Image Segmentation

Abstract: The problem of segmenting a given image into coherent regions is important in Computer Vision and many industrial applications require segmenting a known object into its components. Examples include identifying individual parts of a component for process control work in a manufacturing plant and identifying parts of a car from a photo for automatic damage detection. Unfortunately most of an object's parts of interest in such applications share the same pixel characteristics, having similar colour and texture. This makes segmenting the object into its components a non-trivial task for conventional image segmentation algorithms. In this paper, we propose a "Model Assisted Segmentation" method to tackle this problem. A 3D model of the object is registered over the given image by optimising a novel gradient based loss function. This registration obtains the full 3D pose from an image of the object. The image can have an arbitrary view of the object and is not limited to a particular set of views. The segmentation is subsequently performed using a level-set based method, using the projected contours of the registered 3D model as initialisation curves. The method is fully automatic and requires no user interaction. Also, the system does not require any prior training. We present our results on photographs of a real car.


A framework: Cluster detection and multidimensional visualization of automated data mining using intelligent agents

Abstract: Data Mining techniques plays a vital role like extraction of required knowledge, finding unsuspected information to make strategic decision in a novel way which in term understandable by domain experts. A generalized frame work is proposed by considering non - domain experts during mining process for better understanding, making better decision and better finding new patters in case of selecting suitable data mining techniques based on the user profile by means of intelligent agents. KEYWORDS: Data Mining Techniques, Intelligent Agents, User Profile, Multidimensional Visualization, Knowledge Discovery.


Arduino Tool: For Interactive Artwork Installations

Abstract: The emergence of the digital media and computational tools has widened the doors for creativity. The cutting edge in the digital arts and role of new technologies can be explored for the possible creativity. This gives an opportunity to involve arts with technologies to make creative works. The interactive artworks are often installed in the places where multiple people can interact with the installation, which allows the art to achieve its purpose by allowing the people to observe and involve with the installation. The level of engagement of the audience depends on the various factors such as aesthetic satisfaction, how the audience constructs meaning, pleasure and enjoyment. The method to evaluate these experiences is challenging as it depends on integration between the artificial life and real life by means of human computer interaction. This research investigates "How Adriano fits for creative and interactive artwork installations?" using an artwork installation in the campus of NTNU (Norwegian University of Science & Technology). The main focus of this investigation has been to get an overview on the intersection between information technology and Arts. This gives an opportunity to understand various attributes like creativity, cooperation and openness of processes influencing the creative Artworks. The artwork is combination of Adriano and other auxiliary components such as sensors, LED's and speakers.


Cryptanalysis and enhancement of two low cost rfid authentication protocols

Abstract: Widespread attention is recently paid upon RFID system structure considering its ease of deployment over an extensive range of applications. Due to its several advantages, many technical articles are published to improve its capabilities over specific system implementations. Recently, a lightweight anti-de-synchronization RFID authentication protocol and a lightweight binding proof protocol to guard patient safety are proposed. This contribution provides enough evidence to prove the first introduced protocol vulnerability to de-synchronization attack. It also provides the other protocol's suffering from de-synchronization attack as well as tracking the movements of the tags. This paper also addresses appropriate solutions to fix the security flaws concerning the two described protocols for secure RFID applications.


The Locality of Distributed Symmetry Breaking

Abstract: Symmetry breaking problems are among the most well studied in the field of distributed computing and yet the most fundamental questions about their complexity remain open. In this paper we work in the LOCAL model (where the input graph and underlying distributed network are identical) and study the randomized complexity of four fundamental symmetry breaking problems on graphs: computing MISs (maximal independent sets), maximal matchings, vertex colorings, and ruling sets. A small sample of our results includes - An MIS algorithm running in $O(\log^2\Delta + 2^{O(\sqrt{\log\log n})})$ time, where $\Delta$ is the maximum degree. This is the first MIS algorithm to improve on the 1986 algorithms of Luby and Alon, Babai, and Itai, when $\log n \ll \Delta \ll 2^{\sqrt{\log n}}$, and comes close to the $\Omega(\log \Delta)$ lower bound of Kuhn, Moscibroda, and Wattenhofer. - A maximal matching algorithm running in $O(\log\Delta + \log^4\log n)$ time. This is the first significant improvement to the 1986 algorithm of Israeli and Itai. Moreover, its dependence on $\Delta$ is provably optimal. - A method for reducing symmetry breaking problems in low arboricity/degeneracy graphs to low degree graphs. (Roughly speaking, the arboricity or degeneracy of a graph bounds the density of any subgraph.) Corollaries of this reduction include an $O(\sqrt{\log n})$-time maximal matching algorithm for graphs with arboricity up to $2^{\sqrt{\log n}}$ and an $O(\log^{2/3} n)$-time MIS algorithm for graphs with arboricity up to $2^{(\log n)^{1/3}}$. Each of our algorithms is based on a simple, but powerful technique for reducing a randomized symmetry breaking task to a corresponding deterministic one on a poly$(\log n)$-size graph.


Non-parametric convolution based image-segmentation of ill-posed objects applying context window approach

Abstract: Context-dependence in human cognition process is a well-established fact. Following this, we introduced the image segmentation method that can use context to classify a pixel on the basis of its membership to a particular object-class of the concerned image. In the broad methodological steps, each pixel was defined by its context window (CW) surrounding it the size of which was fixed heuristically. CW texture defined by the intensities of its pixels was convoluted with weights optimized through a non-parametric function supported by a backpropagation network. Result of convolution was used to classify them. The training data points (i.e., pixels) were carefully chosen to include all variety of contexts of types, i) points within the object, ii) points near the edge but inside the objects, iii) points at the border of the objects, iv) points near the edge but outside the objects, v) points near or at the edge of the image frame. Moreover the training data points were selected from all the images within image-dataset. CW texture information for 1000 pixels from face area and background area of images were captured, out of which 700 CWs were used as training input data, and remaining 300 for testing. Our work gives the first time foundation of quantitative enumeration of efficiency of image-segmentation which is extendable to segment out more than 2 objects within an image.


A New Type of Cipher

Abstract: We will define a new type of cipher that doesn't use neither an easy to calcualate and hard to invert matematical function like RSA nor a classical mono or polyalphabetic cipher.