Decoupled execution of synchronous coordination models via behavioural automata

Abstract: Synchronous coordination systems allow the exchange of data by logically indivisible actions involving all coordinated entities. This paper introduces behavioural automata, a logically synchronous coordination model based on the Reo coordination language, which focuses on relevant aspects for the concurrent evolution of these systems. We show how our automata model encodes the Reo and Linda coordination models and how it introduces an explicit predicate that captures the concurrent evolution, distinguishing local from global actions, and lifting the need of most synchronous models to involve all entities at each coordination step, paving the way to more scalable implementations.


Key Predistribution Schemes for Distributed Sensor Networks

Abstract: Key predistribution schemes for distributed sensor networks have received significant attention in the recent literature. In this paper we propose a new construction method for these schemes based on combinations of duals of standard block designs. Our method is a broad spectrum one which works for any intersection threshold. By varying the initial designs, we can generate various schemes and this makes the method quite flexible. We also obtain explicit algebraic expressions for the metrics for local connectivity and resiliency. These schemes are quite efficient with regard to connectivity and resiliency and at the same time they allow a straightforward shared-key discovery.


Grid Information Security Functional Requirement - Fulfilling Information Security of a Smart Grid System

Abstract: This paper describes the background of smart information infrastructure and the needs for smart grid information security. It introduces the conceptual analysis to the methodology with the application of hermeneutic circle and information security functional requirement identification. Information security for the grid market cover matters includes automation and communications industry that affects the operation of electric power systems and the functioning of the utilities that manage them and its awareness of this information infrastructure has become critical to the reliability of the power system. Community benefits from of cost savings, flexibility and deployment along with the establishment of wireless communications. However, concern revolves around the security protections for easily accessible devices such as the smart meter and the related communications hardware. On the other hand, the changing points between traditional versus smart grid networking trend and the information security importance on the communication field reflects the criticality of grid information security functional requirement identification. The goal of this paper is to identify the functional requirement and relate its significance addresses to the consumer requirement of an information security of a smart grid. Vulnerabilities may bring forth possibility for an attacker to penetrate a network, make headway admission to control software, alter it to load conditions that destabilize the grid in unpredictable ways. Focusing on the grid information security functional requirement is stepping ahead in developing consumer trust and satisfaction toward smart grid completeness.


Scaling Inference for Markov Logic with a Task-Decomposition Approach

Abstract: Motivated by applications in large-scale knowledge base construction, we study the problem of scaling up a sophisticated statistical inference framework called Markov Logic Networks (MLNs). Our approach, Felix, uses the idea of Lagrangian relaxation from mathematical programming to decompose a program into smaller tasks while preserving the joint-inference property of the original MLN. The advantage is that we can use highly scalable specialized algorithms for common tasks such as classification and coreference. We propose an architecture to support Lagrangian relaxation in an RDBMS which we show enables scalable joint inference for MLNs. We empirically validate that Felix is significantly more scalable and efficient than prior approaches to MLN inference by constructing a knowledge base from 1.8M documents as part of the TAC challenge. We show that Felix scales and achieves state-of-the-art quality numbers. In contrast, prior approaches do not scale even to a subset of the corpus that is three orders of magnitude smaller.


Adaptive Drift Analysis

Abstract: We show that, for any c>0, the (1+1) evolutionary algorithm using an arbitrary mutation rate p_n = c/n finds the optimum of a linear objective function over bit strings of length n in expected time Theta(n log n). Previously, this was only known for c at most 1. Since previous work also shows that universal drift functions cannot exist for c larger than a certain constant, we instead define drift functions which depend crucially on the relevant objective functions (and also on c itself). Using these carefully-constructed drift functions, we prove that the expected optimisation time is Theta(n log n). By giving an alternative proof of the multiplicative drift theorem, we also show that our optimisation-time bound holds with high probability.


Small witnesses, accepting lassos and winning strategies in omega-automata and games

Abstract: Obtaining accepting lassos, witnesses and winning strategies in omega-automata and games with omega-regular winning conditions is an integral part of many formal methods commonly found in practice today. Despite the fact that in most applications, the lassos, witnesses and strategies found should be as small as possible, little is known about the hardness of obtaining small such certificates. In this paper, we survey the known hardness results and complete the complexity landscape for the cases not considered in the literature so far. We pay particular attention to the approximation hardness of the problems as approximate small solutions usually suffice in practice.


Observational equivalences for linear logic CC languages

Abstract: Linear logic Concurrent Constraint programming (LCC) is an extension of concurrent constraint programming (CC) where the constraint system is based on Girard's linear logic instead of the classical logic. In this paper we address the problem of program equivalence for this programming framework. For this purpose, we present a structural operational semantics for LCC based on a label transition system and investigate different notions of observational equivalences inspired by the state of art of process algebras. Then, we demonstrate that the asynchronous \pi-calculus can be viewed as simple syntactical restrictions of LCC. Finally we show LCC observational equivalences can be transposed straightforwardly to classical Concurrent Constraint languages and Constraint Handling Rules, and investigate the resulting equivalences.


(Co-)Inductive semantics for Constraint Handling Rules

Abstract: In this paper, we address the problem of defining a fixpoint semantics for Constraint Handling Rules (CHR) that captures the behavior of both simplification and propagation rules in a sound and complete way with respect to their declarative semantics. Firstly, we show that the logical reading of states with respect to a set of simplification rules can be characterized by a least fixpoint over the transition system generated by the abstract operational semantics of CHR. Similarly, we demonstrate that the logical reading of states with respect to a set of propagation rules can be characterized by a greatest fixpoint. Then, in order to take advantage of both types of rules without losing fixpoint characterization, we present an operational semantics with persistent. We finally establish that this semantics can be characterized by two nested fixpoints, and we show the resulting language is an elegant framework to program using coinductive reasoning.


Black-Box Complexities of Combinatorial Problems

Abstract: Black-box complexity is a complexity theoretic measure for how difficult a problem is to be optimized by a general purpose optimization algorithm. It is thus one of the few means trying to understand which problems are tractable for genetic algorithms and other randomized search heuristics. Most previous work on black-box complexity is on artificial test functions. In this paper, we move a step forward and give a detailed analysis for the two combinatorial problems minimum spanning tree and single-source shortest paths. Besides giving interesting bounds for their black-box complexities, our work reveals that the choice of how to model the optimization problem is non-trivial here. This in particular comes true where the search space does not consist of bit strings and where a reasonable definition of unbiasedness has to be agreed on.


Cross-moments computation for stochastic context-free grammars

Abstract: In this paper we consider the problem of efficient computation of cross-moments of a vector random variable represented by a stochastic context-free grammar. Two types of cross-moments are discussed. The sample space for the first one is the set of all derivations of the context-free grammar, and the sample space for the second one is the set of all derivations which generate a string belonging to the language of the grammar. In the past, this problem was widely studied, but mainly for the cross-moments of scalar variables and up to the second order. This paper presents new algorithms for computing the cross-moments of an arbitrary order, and the previously developed ones are derived as special cases.


Typesafe Modeling in Text Mining

Abstract: Based on the concept of annotation-based agents, this report introduces tools and a formal notation for defining and running text mining experiments using a statically typed domain-specific language embedded in Scala. Using machine learning for classification as an example, the framework is used to develop and document text mining experiments, and to show how the concept of generic, typesafe annotation corresponds to a general information model that goes beyond text processing.


On Detecting Pollution Attacks in Inter-Session Network Coding

Abstract: Dealing with pollution attacks in inter-session network coding is challenging due to the fact that sources, in addition to intermediate nodes, can be malicious. In this work, we precisely define corrupted packets in inter-session pollution based on the commitment of the source packets. We then propose three detection schemes: one hash-based and two MAC-based schemes: InterMacCPK and SpaceMacPM. InterMacCPK is the first multi-source homomorphic MAC scheme that supports multiple keys. Both MAC schemes can replace traditional MACs, e.g., HMAC, in networks that employ inter-session coding. All three schemes provide in-network detection, are collusion-resistant, and have very low online bandwidth and computation overhead.


A Comprehensive Study of an Online Packet Scheduling Algorithm

Abstract: We study the \emph{bounded-delay model} for Qualify-of-Service buffer management. Time is discrete. There is a buffer. Unit-length jobs (also called \emph{packets}) arrive at the buffer over time. Each packet has an integer release time, an integer deadline, and a positive real value. A packet's characteristics are not known to an online algorithm until the packet actually arrives. In each time step, at most one packet can be sent out of the buffer. The objective is to maximize the total value of the packets sent by their respective deadlines in an online manner. An online algorithm's performance is usually measured in terms of \emph{competitive ratio}, when this online algorithm is compared with a clairvoyant algorithm achieving the best total value. In this paper, we study a simple and intuitive online algorithm. We analyze its performance in terms of competitive ratio for the general model and a few important variants.


Exploiting Agent and Type Independence in Collaborative Graphical Bayesian Games

Abstract: Efficient collaborative decision making is an important challenge for multiagent systems. Finding optimal joint actions is especially challenging when each agent has only imperfect information about the state of its environment. Such problems can be modeled as collaborative Bayesian games in which each agent receives private information in the form of its type. However, representing and solving such games requires space and computation time exponential in the number of agents. This article introduces collaborative graphical Bayesian games (CGBGs), which facilitate more efficient collaborative decision making by decomposing the global payoff function as the sum of local payoff functions that depend on only a few agents. We propose a framework for the efficient solution of CGBGs based on the insight that they posses two different types of independence, which we call agent independence and type independence. In particular, we present a factor graph representation that captures both forms of independence and thus enables efficient solutions. In addition, we show how this representation can provide leverage in sequential tasks by using it to construct a novel method for decentralized partially observable Markov decision processes. Experimental results in both random and benchmark tasks demonstrate the improved scalability of our methods compared to several existing alternatives.


Algorithmic complexity of pair cleaning method for k-satisfiability problem. (draft version)

Abstract: The k-satisfiability problem is a well-known task in computational complexity theory. In this paper approach for it's solving is introduced.


A Methodology for assessing Agile Software Development Approaches

Abstract: Agile methods provide an organization or a team the flexibility to adopt a selected subset of principles and practices based on their culture, their values, and the types of systems that they develop. More specifically, every organization or team implements a customized agile method, tailored to better accommodate its needs. However, the extent to which a customized method supports the organizational objectives, or rather the 'goodness' of that method is questionable. Existing agile assessment approaches focus on a comparative analysis, or are limited in scope and application. In this research, we propose a structured, systematic and comprehensive approach to assess the 'goodness' of agile methods. We examine an agile method based on (1) its adequacy, (2) the capability of the organization to support the adopted principles and practices specified by the method, and (3) the method's effectiveness. We propose the Objectives, Principles and Practices (OPP) Framework to guide our assessment. The Framework identifies (1) objectives of the agile philosophy, (2) principles that support the objectives, (3) practices that are reflective of the principles, (4) the linkages between the objectives, principles and practices, and (5) indicators for each practice to assess the effectiveness of the practice and the extent to which the organization supports its implementation. In this document, we discuss our solution approach, preliminary results, and future work.


Innocent strategies as presheaves and interactive equivalences for CCS

Abstract: Seeking a general framework for reasoning about and comparing programming languages, we derive a new view of Milner's CCS. We construct a category E of plays, and a subcategory V of views. We argue that presheaves on V adequately represent innocent strategies, in the sense of game semantics. We then equip innocent strategies with a simple notion of interaction. This results in an interpretation of CCS. Based on this, we propose a notion of interactive equivalence for innocent strategies, which is close in spirit to Beffara's interpretation of testing equivalences in concurrency theory. In this framework we prove that the analogues of fair and must testing equivalences coincide, while they differ in the standard setting.


Interaction and observation, categorically

Abstract: This paper proposes to use dialgebras to specify the semantics of interactive systems in a natural way. Dialgebras are a conservative extension of coalgebras. In this categorical model, from the point of view that we provide, the notions of observation and interaction are separate features. This is useful, for example, in the specification of process equivalences, which are obtained as kernels of the homomorphisms of dialgebras. As an example we present the asynchronous semantics of the CCS.


Structured Operational Semantics for Graph Rewriting

Abstract: Process calculi and graph transformation systems provide models of reactive systems with labelled transition semantics. While the semantics for process calculi is compositional, this is not the case for graph transformation systems, in general. Hence, the goal of this article is to obtain a compositional semantics for graph transformation system in analogy to the structural operational semantics (SOS) for Milner's Calculus of Communicating Systems (CCS). The paper introduces an SOS style axiomatization of the standard labelled transition semantics for graph transformation systems. The first result is its equivalence with the so-called Borrowed Context technique. Unfortunately, the axiomatization is not compositional in the expected manner as no rule captures "internal" communication of sub-systems. The main result states that such a rule is derivable if the given graph transformation system enjoys a certain property, which we call "complementarity of actions". Archetypal examples of such systems are interaction nets. We also discuss problems that arise if "complementarity of actions" is violated.


Polymorphic Endpoint Types for Copyless Message Passing

Abstract: We present PolySing#, a calculus that models process interaction based on copyless message passing, in the style of Singularity OS. We equip the calculus with a type system that accommodates polymorphic endpoint types, which are a variant of polymorphic session types, and we show that well-typed processes are free from faults, leaks, and communication errors. The type system is essentially linear, although linearity alone may leave room for scenarios where well-typed processes leak memory. We identify a condition on endpoint types that prevents these leaks from occurring.


On the reaction time of some synchronous systems

Abstract: This paper presents an investigation of the notion of reaction time in some synchronous systems. A state-based description of such systems is given, and the reaction time of such systems under some classic composition primitives is studied. Reaction time is shown to be non-compositional in general. Possible solutions are proposed, and applications to verification are discussed. This framework is illustrated by some examples issued from studies on real-time embedded systems.


Correlating Formal Semantic Models of Reo Connectors: Connector Coloring and Constraint Automata

Abstract: Over the past decades, coordination languages have emerged for the specification and implementation of interaction protocols for communicating software components. This class of languages includes Reo, a platform for compositional construction of connectors. In recent years, various formalisms for describing the behavior of Reo connectors have come to existence, each of them serving its own purpose. Naturally, questions about how these models relate to each other arise. From a theoretical point of view, answers to these questions provide us with better insight into the fundamentals of Reo, while from a more practical perspective, these answers broaden the applicability of Reo's development tools. In this paper, we address one of these questions: we investigate the equivalence between coloring models and constraint automata, the two most dominant and practically relevant semantic models of Reo. More specifically, we define operators that transform one model to the other (and vice versa), prove their correctness, and show that they distribute over composition. To ensure that the transformation operators map one-to-one (instead of many-to-one), we extend coloring models with data constraints. Though primarily a theoretical contribution, we sketch some potential applications of our results: the broadening of the applicability of existing tools for connector verification and animation.


Amending Contracts for Choreographies

Abstract: Distributed interactions can be suitably designed in terms of choreographies. Such abstractions can be thought of as global descriptions of the coordination of several distributed parties. Global assertions define contracts for choreographies by annotating multiparty session types with logical formulae to validate the content of the exchanged messages. The introduction of such constraints is a critical design issue as it may be hard to specify contracts that allow each party to be able to progress without violating the contract. In this paper, we propose three methods that automatically correct inconsistent global assertions. The methods are compared by discussing their applicability and the relationships between the amended global assertions and the original (inconsistent) ones.


Contracts in distributed systems

Abstract: We present a parametric calculus for contract-based computing in distributed systems. By abstracting from the actual contract language, our calculus generalises both the contracts-as-processes and contracts-as-formulae paradigms. The calculus features primitives for advertising contracts, for reaching agreements, and for querying the fulfilment of contracts. Coordination among principals happens via multi-party sessions, which are created once agreements are reached. We present two instances of our calculus, by modelling contracts as (i) processes in a variant of CCS, and (ii) as formulae in a logic. With the help of a few examples, we discuss the primitives of our calculus, as well as some possible variants.


Specifying and Staging Mixed-Initiative Dialogs with Program Generation and Transformation

Abstract: Specifying and implementing flexible human-computer dialogs, such as those used in kiosks and smart phone apps, is challenging because of the numerous and varied directions in which each user might steer a dialog. The objective of this research is to improve dialog specification and implementation. To do so we enriched a notation based on concepts from programming languages, especially partial evaluation, for specifying a variety of unsolicited reporting, mixed-initiative dialogs in a concise representation that serves as a design for dialog implementation. We also built a dialog mining system that extracts a specification in this notation from requirements. To demonstrate that such a specification provides a design for dialog implementation, we built a system that automatically generates an implementation of the dialog, called a stager, from it. These two components constitute a dialog modeling toolkit that automates dialog specification and implementation. These results provide a proof of concept and demonstrate the study of dialog specification and implementation from a programming languages perspective. The ubiquity of dialogs in domains such as travel, education, and health care combined with the demand for smart phone apps provide a landscape for further investigation of these results.


Symmetric Connectivity with Directional Antennas

Abstract: Let P be a set of points in the plane, representing directional antennas of angle a and range r. The coverage area of the antenna at point p is a circular sector of angle a and radius r, whose orientation is adjustable. For a given orientation assignment, the induced symmetric communication graph (SCG) of P is the undirected graph that contains the edge (u,v) iff v lies in u's sector and vice versa. In this paper we ask what is the smallest angle a for which there exists an integer n=n(a), such that for any set P of n antennas of angle a and unbounded range, one can orient the antennas so that the induced SCG is connected, and the union of the corresponding wedges is the entire plane. We show that the answer to this problem is a=\pi/2, for which n=4. Moreover, we prove that if Q_1 and Q_2 are quadruplets of antennas of angle \pi/2 and unbounded range, separated by a line, to which one applies the above construction, independently, then the induced SCG of Q_1 \cup Q_2 is connected. This latter result enables us to apply the construction locally, and to solve the following two further problems. In the first problem, we are given a connected unit disk graph (UDG), corresponding to a set P of omni-directional antennas of range 1, and the goal is to replace these antennas by directional antennas of angle \pi/2 and range r=O(1) and to orient them, such that the induced SCG is connected, and, moreover, is an O(1)-spanner of the UDG, w.r.t. hop distance. In our solution r = 14\sqrt{2} and the spanning ratio is 8. In the second problem, we are given a set P of directional antennas of angle \pi/2 and adjustable range. The goal is to assign to each antenna p, an orientation and a range r_p, such that the resulting SCG is connected, and \sum_{p \in P} r_p^\beta is minimized, where \beta \ge 1 is a constant. We present an O(1)-approximation algorithm.


An Efficient Real Time Method of Fingertip Detection

Abstract: Fingertips detection has been used in many applications, and it is very popular and commonly used in the area of Human Computer Interaction these days. This paper presents a novel time efficient method that will lead to fingertip detection after cropping the irrelevant parts of input image. Binary silhouette of the input image is generated using HSV color space based skin filter and hand cropping done based on histogram of the hand image. The cropped image will be used to figure out the fingertips.


Towards an Optimal Space-and-Query-Time Index for Top-k Document Retrieval

Abstract: Let $\D = $$ \{d_1,d_2,...d_D\}$ be a given set of $D$ string documents of total length $n$, our task is to index $\D$, such that the $k$ most relevant documents for an online query pattern $P$ of length $p$ can be retrieved efficiently. We propose an index of size $|CSA|+n\log D(2+o(1))$ bits and $O(t_{s}(p)+k\log\log n+poly\log\log n)$ query time for the basic relevance metric \emph{term-frequency}, where $|CSA|$ is the size (in bits) of a compressed full text index of $\D$, with $O(t_s(p))$ time for searching a pattern of length $p$ . We further reduce the space to $|CSA|+n\log D(1+o(1))$ bits, however the query time will be $O(t_s(p)+k(\log \sigma \log\log n)^{1+\epsilon}+poly\log\log n)$, where $\sigma$ is the alphabet size and $\epsilon >0$ is any constant.


On Berry's conjectures about the stable order in PCF

Abstract: PCF is a sequential simply typed lambda calculus language. There is a unique order-extensional fully abstract cpo model of PCF, built up from equivalence classes of terms. In 1979, G\'erard Berry defined the stable order in this model and proved that the extensional and the stable order together form a bicpo. He made the following two conjectures: 1) "Extensional and stable order form not only a bicpo, but a bidomain." We refute this conjecture by showing that the stable order is not bounded complete, already for finitary PCF of second-order types. 2) "The stable order of the model has the syntactic order as its image: If a is less than b in the stable order of the model, for finite a and b, then there are normal form terms A and B with the semantics a, resp. b, such that A is less than B in the syntactic order." We give counter-examples to this conjecture, again in finitary PCF of second-order types, and also refute an improved conjecture: There seems to be no simple syntactic characterization of the stable order. But we show that Berry's conjecture is true for unary PCF. For the preliminaries, we explain the basic fully abstract semantics of PCF in the general setting of (not-necessarily complete) partial order models (f-models.) And we restrict the syntax to "game terms", with a graphical representation.


A Group Signature Based Electronic Toll Pricing System

Abstract: With the prevalence and development of GNSS technologies, location-based vehicle services (LBVS) have experienced a rapid growth in recent years. However, location is a sensitive and private piece of information, so the design and development of such services just take the clients' privacy concerns into account. In this paper, we propose a new electronic toll pricing system based on group signatures, which provides a strong guarantee for the clients' anonymity within groups. Our system achieves a balance between privacy and the communication overhead imposed upon the users.


Proposal for improvement in the transfer and execution of multiple instances of a virtual image

Abstract: Virtualization technology allows currently any application run any application complex and expensive computational (the scientific applications are a good example) on heterogeneous distributed systems, which make regular use of Grid and Cloud technologies, enabling significant savings in computing time. This model is particularly interesting for the mass execution of scientific simulations and calculations, allowing parallel execution of applications using the same execution environment (unchanged) used by the scientist as usual. However, the use and distribution of large virtual images can be a problem (up to tens of GBytes), which is aggravated when attempting a mass mailing on a large number of distributed computers. This work has as main objective to present an analysis of how implementation and a proposal for the improvement (reduction in size) of the virtual images pretending reduce distribution time in distributed systems. This analysis is done very specific requirements that need an operating system (guest OS) on some aspects of its execution.


Serialising the ISO SynAF Syntactic Object Model

Abstract: This paper introduces, an XML format developed to serialise the object model defined by the ISO Syntactic Annotation Framework SynAF. Based on widespread best practices we adapt a popular XML format for syntactic annotation, TigerXML, with additional features to support a variety of syntactic phenomena including constituent and dependency structures, binding, and different node types such as compounds or empty elements. We also define interfaces to other formats and standards including the Morpho-syntactic Annotation Framework MAF and the ISOCat Data Category Registry. Finally a case study of the German Treebank TueBa-D/Z is presented, showcasing the handling of constituent structures, topological fields and coreference annotation in tandem.


Policy Creation Model for Policy-Based Management in Telecommunications Networks

Abstract: Policy-based management (PBM) is being used as technological solution on the managing and controlling complex networks and systems. One of the most important issues involved in the life-cycle of PBM is the policies creation because the future decisions made by the management system depend on this, and therefore, the network behavior. In this paper we present a novel model for creating management policies in telecommunications networks. We propose a model which includes a Policy Creation Process, Actors, Policy Abstraction Levels and a Procedure for Creating Policies. An implementation of the proposed model over the Technology Division at University of Cauca is included.


Estudo de Viabilidade de uma Plataforma de Baixo Custo para Data Warehouse

Abstract: Often corporations need tools to improve their decision making in a competitive market. In general, these tools are based on data warehouse platforms to mange and analyze large amounts of data. However, several of these corporations do not have enough resources to buy such platforms because of the high cost. This work is dedicated to a feasibility study of a low cost platform to data warehouse. We consider as a low cost platform the use of open source software like the PostgreSQL database system and the GNU/Linux operational system. We verify the feasibility of this platform by executing two benchmarks that simulate a data warehouse workload. The workload reproduces a multi-user environment with the execution of complex queries, which executes: aggregations, nested sub queries, multi joins, in-line views and more. Considering the results we were able to highlight some problems on the PostgreSQL database system, and discuss improvements in the context of data warehouse.


A Novel Trajectory Clustering technique for selecting cluster heads in Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) suffers from the hot spot problem where the sensor nodes closest to the base station are need to relay more packet than the nodes farther away from the base station. Thus, lifetime of sensory network depends on these closest nodes. Clustering methods are used to extend the lifetime of a wireless sensor network. However, current clustering algorithms usually utilize two techniques; selecting cluster heads with more residual energy, and rotating cluster heads periodically to distribute the energy consumption among nodes in each cluster and lengthen the network lifetime. Most of the algorithms use random selection for selecting the cluster heads. Here, we propose a novel trajectory clustering technique for selecting the cluster heads in WSNs. Our algorithm selects the cluster heads based on traffic and rotates periodically. It provides the first trajectory based clustering technique for selecting the cluster heads and to extenuate the hot spot problem by prolonging the network lifetime.


Enhanced User Authentication through Trajectory Clustering

Abstract: Password authentication is the most commonly used technique to authenticate the user validity. However, due to its simplicity, it is vulnerable to pseudo attacks. It can be enhanced using various biometric techniques such as thumb impression, finger movement, eye movement etc. In this paper, we concentrate on the most economic technique, based on the user habitual rhythm pattern i.e. not what they type but how they type is the measure for authenticating the user. We consider the latency between key events as the trajectory, and trajectory clustering is used to obtain the hidden patterns of the user. Obtained pattern can be considered as a cluster of measurements that can be used to differentiate from other users. We evaluated the proposed technique on the data obtained from the 100 users.


A Hybrid Trajectory Clustering for Predicting User Navigation


A Fault Tolerant Trajectory Clustering (FTTC) for selecting cluster heads inWireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) suffers from the hot spot problem where the sensor nodes closest to the base station are need to relay more packet than the nodes farther away from the base station. Thus, lifetime of sensory network depends on these closest nodes. Clustering methods are used to extend the lifetime of a wireless sensor network. However, current clustering algorithms usually utilize two techniques; selecting cluster heads with more residual energy, and rotating cluster heads periodically to distribute the energy consumption among nodes in each cluster and lengthen the network lifetime. Most of the algorithms use random selection for selecting the cluster heads. Here, we propose a Fault Tolerant Trajectory Clustering (FTTC) technique for selecting the cluster heads in WSNs. Our algorithm selects the cluster heads based on traffic and rotates periodically. It provides the first Fault Tolerant Trajectory based clustering technique for selecting the cluster heads and to extenuate the hot spot problem by prolonging the network lifetime.


Binary Particle Swarm Optimization based Biclustering of Web usage Data

Abstract: Web mining is the nontrivial process to discover valid, novel, potentially useful knowledge from web data using the data mining techniques or methods. It may give information that is useful for improving the services offered by web portals and information access and retrieval tools. With the rapid development of biclustering, more researchers have applied the biclustering technique to different fields in recent years. When biclustering approach is applied to the web usage data it automatically captures the hidden browsing patterns from it in the form of biclusters. In this work, swarm intelligent technique is combined with biclustering approach to propose an algorithm called Binary Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The main objective of this algorithm is to retrieve the global optimal bicluster from the web usage data. These biclusters contain relationships between web users and web pages which are useful for the E-Commerce applications like web advertising and marketing. Experiments are conducted on real dataset to prove the efficiency of the proposed algorithms.


Distributed Agreement in Dynamic Peer-to-Peer Networks

Abstract: Motivated by the need for robust and fast distributed computation in highly dynamic Peer-to-Peer (P2P) networks, we study algorithms for the fundamental distributed agreement problem. P2P networks are highly dynamic networks that experience heavy node {\em churn}. Our goal is to design fast algorithms (running in a small number of rounds) that guarantee, despite high node churn rate, that almost all nodes reach a stable agreement. Our main contributions are randomized distributed algorithms that guarantee {\em stable almost-everywhere agreement} with high probability even under high adversarial churn in a polylogarithmic number of rounds: 1. An $O(\log^2 n)$-round ($n$ is the stable network size) randomized algorithm that achieves almost-everywhere agreement with high probability under up to {\em linear} churn {\em per round} (i.e., $\epsilon n$, for some small constant $\epsilon > 0$), assuming that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm). Our algorithm requires only polylogarithmic in $n$ bits to be processed and sent (per round) by each node. 2. An $O(\log m\log^3 n)$-round randomized algorithm that achieves almost-everywhere agreement with high probability under up to $\epsilon \sqrt{n}$ churn per round (for some small $\epsilon > 0$), where $m$ is the size of the input value domain, that works even under an adaptive adversary (that also knows the past random choices made by the algorithm). This algorithm requires up to polynomial in $n$ bits (and up to $O(\log m)$ bits) to be processed and sent (per round) by each node.


Scheduling partially ordered jobs faster than 2^n

Abstract: In the SCHED problem we are given a set of n jobs, together with their processing times and precedence constraints. The task is to order the jobs so that their total completion time is minimized. SCHED is a special case of the Traveling Repairman Problem with precedences. A natural dynamic programming algorithm solves both these problems in 2^n n^O(1) time, and whether there exists an algorithms solving SCHED in O(c^n) time for some constant c < 2 was an open problem posted in 2004 by Woeginger. In this paper we answer this question positively.


Towards Spatio-Temporal SOLAP

Abstract: The integration of Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP), denoted SOLAP, is aimed at exploring and analyzing spatial data. In real-world SOLAP applications, spatial and non-spatial data are subject to changes. In this paper we present a temporal query language for SOLAP, called TPiet-QL, supporting so-called discrete changes (for example, in land use or cadastral applications there are situations where parcels are merged or split). TPiet-QL allows expressing integrated GIS-OLAP queries in an scenario where spatial objects change across time.


Approximate Bregman near neighbors in sublinear time: Beyond the triangle inequality

Abstract: In this paper we present the first provable approximate nearest-neighbor (ANN) algorithms for Bregman divergences. Our first algorithm processes queries in O(log^d n) time using O(n log^d n) space and only uses general properties of the underlying distance function (which includes Bregman divergences as a special case). The second algorithm processes queries in O(log n) time using O(n) space and exploits structural constants associated specifically with Bregman divergences. An interesting feature of our algorithms is that they extend the ring-tree + quad-tree paradigm for ANN searching beyond Euclidean distances and metrics of bounded doubling dimension to distances that might not even be symmetric or satisfy a triangle inequality.


Towards Optimal Sorting of 16 Elements

Abstract: One of the fundamental problem in the theory of sorting is to find the pessimistic number of comparisons sufficient to sort a given number of elements. Currently 16 is the lowest number of elements for which we do not know the exact value. We know that 46 comparisons suffices and that 44 do not. There is an open question if 45 comparisons are sufficient. We present an attempt to resolve that problem by performing an exhaustive computer search. We also present an algorithm for counting linear extensions which substantially speeds up computations.


Evader Interdiction and Collateral Damage

Abstract: In network interdiction problems, evaders (e.g., hostile agents or data packets) may be moving through a network towards targets and we wish to choose locations for sensors in order to intercept the evaders before they reach their destinations. The evaders might follow deterministic routes or Markov chains, or they may be reactive}, i.e., able to change their routes in order to avoid sensors placed to detect them. The challenge in such problems is to choose sensor locations economically, balancing security gains with costs, including the inconvenience sensors inflict upon innocent travelers. We study the objectives of 1) maximizing the number of evaders captured when limited by a budget on sensing cost and 2) capturing all evaders as cheaply as possible. We give optimal sensor placement algorithms for several classes of special graphs and hardness and approximation results for general graphs, including for deterministic or Markov chain-based and reactive or oblivious evaders. In a similar-sounding but fundamentally different problem setting posed by Rubinstein and Glazer where both evaders and innocent travelers are reactive, we again give optimal algorithms for special cases and hardness and approximation results on general graphs.


UWB Array Design Using Variable Zo Technology and Central Force Optimization

Abstract: This note applies Variable Zo technology to the design of an Ultra Wideband (UWB) Yagi-Uda array optimized using Central Force Optimization. Variable Zo is a novel and proprietary approach to antenna design and optimization that treats the feed system characteristic impedance, Zo, as a design variable instead of a fixed design parameter as is traditionally done. Variable Zo is applicable to any antenna design or optimization methodology, and using it will generally produce better antenna designs across any user-specified set of performance objectives.


Optimal Base Station Placement: A Stochastic Method Using Interference Gradient In Downlink Case

Abstract: In this paper, we study the optimal placement and optimal number of base stations added to an existing wireless data network through the interference gradient method. This proposed method considers a sub-region of the existing wireless data network, hereafter called region of interest. In this region, the provider wants to increase the network coverage and the users throughput. In this aim, the provider needs to determine the optimal number of base stations to be added and their optimal placement. The proposed approach is based on the Delaunay triangulation of the region of interest and the gradient descent method in each triangle to compute the minimum interference locations. We quantify the increase of coverage and throughput.


Network Localization on Unit Disk Graphs

Abstract: We study the problem of cooperative localization of a large network of nodes in integer-coordinated unit disk graphs, a simplified but useful version of general random graph. Exploiting the property that the radius $r$ sets clear cut on the connectivity of two nodes, we propose an essential philosophy that "no connectivity is also useful information just like the information being connected" in unit disk graphs. Exercising this philosophy, we show that the conventional network localization problem can be re-formulated to significantly reduce the search space, and that global rigidity, a necessary and sufficient condition for the existence of unique solution in general graphs, is no longer necessary. While the problem is still NP-hard, we show that a (depth-first) tree-search algorithm with memory O(N) ($N$ is the network size) can be developed, and for practical setups, the search complexity and speed is very manageable, and is magnitudes less than the conventional problem, especially when the graph is sparse or when only very limited anchor nodes are available.


Turing degrees of multidimensional SFTs

Abstract: In this paper we are interested in computability aspects of subshifts and in particular Turing degrees of 2-dimensional SFTs (i.e. tilings). To be more precise, we prove that given any \pizu subset $P$ of $\{0,1\}^\NN$ there is a SFT $X$ such that $P\times\ZZ^2$ is recursively homeomorphic to $X\setminus U$ where $U$ is a computable set of points. As a consequence, if $P$ contains a recursive member, $P$ and $X$ have the exact same set of Turing degrees. On the other hand, we prove that if $X$ contains only non-recursive members, some of its members always have different but comparable degrees. This gives a fairly complete study of Turing degrees of SFTs.


A Data Mining Approach to the Diagnosis of Tuberculosis by Cascading Clustering and Classification

Abstract: In this paper, a methodology for the automated detection and classification of Tuberculosis(TB) is presented. Tuberculosis is a disease caused by mycobacterium which spreads through the air and attacks low immune bodies easily. Our methodology is based on clustering and classification that classifies TB into two categories, Pulmonary Tuberculosis(PTB) and retroviral PTB(RPTB) that is those with Human Immunodeficiency Virus (HIV) infection. Initially K-means clustering is used to group the TB data into two clusters and assigns classes to clusters. Subsequently multiple different classification algorithms are trained on the result set to build the final classifier model based on K-fold cross validation method. This methodology is evaluated using 700 raw TB data obtained from a city hospital. The best obtained accuracy was 98.7% from support vector machine (SVM) compared to other classifiers. The proposed approach helps doctors in their diagnosis decisions and also in their treatment planning procedures for different categories.


Wireless Capacity With Arbitrary Gain Matrix

Abstract: Given a set of wireless links, a fundamental problem is to find the largest subset that can transmit simultaneously, within the SINR model of interference. Significant progress on this problem has been made in recent years. In this note, we study the problem in the setting where we are given a fixed set of arbitrary powers each sender must use, and an arbitrary gain matrix defining how signals fade. This variation of the problem appears immune to most algorithmic approaches studied in the literature. Indeed it is very hard to approximate since it generalizes the max independent set problem. Here, we propose a simple semi-definite programming approach to the problem that yields constant factor approximation, if the optimal solution is strictly larger than half of the input size.


Conauto-2.0: Fast Isomorphism Testing and Automorphism Group Computation

Abstract: In this paper we present an algorithm, called conauto-2.0, that can efficiently compute a set of generators of the automorphism group of a graph, and test whether two graphs are isomorphic, finding an isomorphism if they are. This algorithm uses the basic individualization/refinement technique, and is an improved version of the algorithm conauto, which has been shown to be very fast for random graphs and several families of hard graphs. In this paper, it is proved that, under some circumstances, it is not only possible to prune the search space (using already found generators of the automorphism group), but also to infer new generators without the need of explicitly finding an automorphism of the graph. This result is especially suited for graphs with regularly connected components, and can be applied in any isomorphism testing and canonical labeling algorithm (that use the individualization/refinement technique) to significantly improve its performance. Additionally, a dynamic target cell selection function is used to adapt to different graphs. The resulting algorithm preserves all the nice features of conauto, but reduces the time for testing graphs with regularly connected components and other hard graph families. We run extensive experiments, which show that the most popular algorithms (namely, nauty, bliss, Traces, and saucy) are slower than conauto-2.0, among others, for the graph families based on components.


Onset of coherent attitude layers in a population of sports fans

Abstract: The aim of this paper was to empirically investigate the behavior of fans, globally coupled to a common environmental source of information. The environmental stimuli were given in a form of referee's decisions list. The sample of fans had to respond on each stimulus by associating points signifying his/her own opinion, emotion and action that referee's decisions provoke. Data were fitted by the Brillouin function which was a solution of an adapted model of quantum statistical physics to social phenomena. Correlation and a principal component analysis were performed in order to detect any collective behavior of the social ensemble of fans. Results showed that fans behaved as a system subject to a phase transition where the neutral state in the opinion, emotional and action space has been destabilized and a new stable state of coherent attitudes was formed. The enhancement of fluctuations and the increase of social susceptibility (responsiveness) to referee's decisions were connected to the first few decisions. The subsequent reduction of values in these parameters signified the onset of coherent layering within the attitude space of the social ensemble of fans. In the space of opinions fan coherence was maximal as only one layer of coherence emerged. In the emotional and action spaces the number of coherent levels was 2 and 4 respectively. The principal component analysis revealed a strong collective behavior and a high degree of integration within and between the opinion, emotional and action spaces of the sample of fans. These results point to one possible way of how different proto-groups, violent and moderate, may be formed as a consequence of global coupling to a common source of information.


DANCE: A Framework for the Distributed Assessment of Network Centralities

Abstract: The analysis of large-scale complex networks is a major challenge in the Big Data domain. Given the large-scale of the complex networks researchers commonly deal with nowadays, the use of localized information (i.e. restricted to a limited neighborhood around each node of the network) for centrality-based analysis is gaining momentum in the recent literature. In this context, we propose a framework for the Distributed Assessment of Network Centralities (DANCE) in complex networks. DANCE offers a single environment that allows the use of different localized centrality proposals, which can be tailored to specific applications. This environment can be thus useful given the vast potential applicability of centrality-based analysis on large-scale complex networks found in different areas, such as Biology, Physics, Sociology, or Computer Science. Since the localized centrality proposals DANCE implements employ only localized information, DANCE can easily benefit from parallel processing environments and run on different computing architectures. To illustrate this, we present a parallel implementation of DANCE and show how it can be applied to the analysis of large-scale complex networks using different kinds of network centralities. This implementation is made available to complex network researchers and practitioners interested in using it through a scientific web portal.


Stateful Testing: Finding More Errors in Code and Contracts

Abstract: Automated random testing has shown to be an effective approach to finding faults but still faces a major unsolved issue: how to generate test inputs diverse enough to find many faults and find them quickly. Stateful testing, the automated testing technique introduced in this article, generates new test cases that improve an existing test suite. The generated test cases are designed to violate the dynamically inferred contracts (invariants) characterizing the existing test suite. As a consequence, they are in a good position to detect new errors, and also to improve the accuracy of the inferred contracts by discovering those that are unsound. Experiments on 13 data structure classes totalling over 28,000 lines of code demonstrate the effectiveness of stateful testing in improving over the results of long sessions of random testing: stateful testing found 68.4% new errors and improved the accuracy of automatically inferred contracts to over 99%, with just a 7% time overhead.


Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition

Abstract: We employ the face recognition technology developed in house at face.com to a well accepted benchmark and show that without any tuning we are able to considerably surpass state of the art results. Much of the improvement is concentrated in the high-valued performance point of zero false positive matches, where the obtained recall rate almost doubles the best reported result to date. We discuss the various components and innovations of our system that enable this significant performance gap. These components include extensive utilization of an accurate 3D reconstructed shape model dealing with challenges arising from pose and illumination. In addition, discriminative models based on billions of faces are used in order to overcome aging and facial expression as well as low light and overexposure. Finally, we identify a challenging set of identification queries that might provide useful focus for future research.


13/9-approximation for Graphic TSP

Abstract: The Travelling Salesman Problem is one the most fundamental and most studied problems in approximation algorithms. For more than 30 years, the best algorithm known for general metrics has been Christofides's algorithm with approximation factor of 3/2, even though the so-called Held-Karp LP relaxation of the problem is conjectured to have the integrality gap of only 4/3. Very recently, significant progress has been made for the important special case of graphic metrics, first by Oveis Gharan et al., and then by Momke and Svensson. In this paper, we provide an improved analysis for the approach introduced by Momke and Svensson yielding a bound of 13/9 on the approximation factor, as well as a bound of 19/12+epsilon for any epsilon>0 for a more general Travelling Salesman Path Problem in graphic metrics.


Development and Deployment of Fixed Wireless Access in South West Nigeria: Performance and Evaluation

Abstract: Fixed Wireless Access (FWA) involves the use of wireless technology to replace copper to connect subscribers to the telephone network. It is a variant of wireless broadband which provides an alternative in the so-called 'last mile' connectivity between the subscriber and the fixed telecommunications network. FWA could either be narrowband or broadband and it is predominantly deployed using the Code Division Multiple Access (CDMA) technology. In assessing the extent of development and deployment of FWA, the perspective of the operators and users was elicited primarily through the use of questionnaires. Issues like setup cost, tax, Government incentive, availability of infrastructure and manpower applied to the operators while on the users' part factors like quality of service, signal strength as well as call rate were considered. The South western zone of Nigeria is regarded as one of the most urbanized regions in the south of Sahara, this is not out of place considering the fact that Lagos which is the nation's commercial nerve centre and a mega-city is located within this region. The scope of this research covered this very lively part of the country. The relationship between the parameters or variables considered was established using an appropriate statistical method: The Regression analysis. In terms of users' preference, Global System of Mobile communication (GSM) was compared with FWA. Results were interpreted and suitable conclusions were drawn to wrap up a quite revealing work.


The Impact of Information Technology in Nigeria's Banking Industry

Abstract: Today, information technology (IT) has become a key element in economic development and a backbone of knowledge-based economies in terms of operations, quality delivery of services and productivity of services. Therefore, taking advantage of information technologies (IT) is an increasing challenge for developing countries. There is now growing evidence that Knowledge-driven innovation is a decisive factor in the competitiveness of nations, industries, organizations and firms. Organizations like the banking sector have benefited substantially from e-banking, which is one among the IT applications for strengthening the competitiveness. This paper presents the current trend in the application of IT in the banking industries in Nigeria and gives an insight into how quality banking has been enhanced via IT. The paper further reveals that the deployment of IT facilities in the Nigerian Banking industry has brought about fundamental changes in the content and quality of banking business in the country. This analysis and clarification of how Nigerian Banks have used IT to reengineer their operations is detailed through literature review and observation. Three categories of variables that relate to the use and implementation of information technology devices were considered in this paper. These include the nature and degree of adoption of innovative technologies; degree of utilization of the identified technologies; and the impact of the adoption of IT devices on the bank operations.


Development of a Window Based Security System for Electronic Data Interchange

Abstract: The Electronic Data Interchange (EDI) is the exchange of standardized documents between computer systems for business use. The objective of this study is to make Electronic Data Interchange secure to use and to eliminate human intervention in the transfer of data between business partners so that productivity and efficiency can be improved and also promote its usage between two or more trading organizations. This paper provides an overview of EDI by describing the traditional problems of exchanging information in business environments and how the EDI solves those problems and gives benefits to the company that makes use of EDI. This paper also introduces the common EDI Standards and explains how it works, how it is used over the internet and the security measures implemented. The system was executed on both local area network and wide area network after a critical study of the existing EDI methods and also implemented using VB.Net programming language. Finally, an interactive program was developed that handles the transfer of files, with special attention to the security of the items that are being transferred from one computer workstation to another.


Learning Representations by Maximizing Compression

Abstract: We give an algorithm that learns a representation of data through compression. The algorithm 1) predicts bits sequentially from those previously seen and 2) has a structure and a number of computations similar to an autoencoder. The likelihood under the model can be calculated exactly, and arithmetic coding can be used directly for compression. When training on digits the algorithm learns filters similar to those of restricted boltzman machines and denoising autoencoders. Independent samples can be drawn from the model by a single sweep through the pixels. The algorithm has a good compression performance when compared to other methods that work under random ordering of pixels.


Combinatorial Algorithms for Capacitated Network Design

Abstract: We focus on designing combinatorial algorithms for the Capacitated Network Design problem (Cap-SNDP). The Cap-SNDP is the problem of satisfying connectivity requirements when edges have costs and hard capacities. We begin by showing that the Group Steiner tree problem (GST) is a special case of Cap-SNDP even when there is connectivity requirement between only one source-sink pair. This implies the first poly-logarithmic lower bound for the Cap-SNDP. We next provide combinatorial algorithms for several special cases of this problem. The Cap-SNDP is equivalent to its special case when every edge has either zero cost or infinite capacity. We consider a special case, called Connected Cap-SNDP, where all infinite-capacity edges in the solution are required to form a connected component containing the sinks. This problem is motivated by its similarity to the Connected Facility Location problem [G+01,SW04]. We solve this problem by reducing it to Submodular tree cover problem, which is a common generalization of Connected Cap-SNDP and Group Steiner tree problem. We generalize the recursive greedy algorithm [CEK] achieving a poly-logarithmic approximation algorithm for Submodular tree cover problem. This result is interesting in its own right and gives the first poly-logarithmic approximation algorithms for Connected hard capacities set multi-cover and Connected source location. We then study another special case of Cap-SNDP called Unbalanced point-to-point connection problem. Besides its practical applications to shift design problems [EKS], it generalizes many problems such as k-MST, Steiner Forest and Point-to-Point Connection. We give a combinatorial logarithmic approximation algorithm for this problem by reducing it to degree-bounded SNDP.


An index for regular expression queries: Design and implementation

Abstract: The like regular expression predicate has been part of the SQL standard since at least 1989. However, despite its popularity and wide usage, database vendors provide only limited indexing support for regular expression queries which almost always require a full table scan. In this paper we propose a rigorous and robust approach for providing indexing support for regular expression queries. Our approach consists of formulating the indexing problem as a combinatorial optimization problem. We begin with a database, abstracted as a collection of strings. From this data set we generate a query workload. The input to the optimization problem is the database and the workload. The output is a set of multigrams (substrings) which can be used as keys to records which satisfy the query workload. The multigrams can then be integrated with the data structure (like B+ trees) to provide indexing support for the queries. We provide a deterministic and a randomized approximation algorithm (with provable guarantees) to solve the optimization problem. Extensive experiments on synthetic data sets demonstrate that our approach is accurate and efficient. We also present a case study on PROSITE patterns - which are complex regular expression signatures for classes of proteins. Again, we are able to demonstrate the utility of our indexing approach in terms of accuracy and efficiency. Thus, perhaps for the first time, there is a robust and practical indexing mechanism for an important class of database queries.


Unilateral Altruism in Network Routing Games with Atomic Players

Abstract: We study a routing game in which one of the players unilaterally acts altruistically by taking into consideration the latency cost of other players as well as his own. By not playing selfishly, a player can not only improve the other players' equilibrium utility but also improve his own equilibrium utility. To quantify the effect, we define a metric called the Value of Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the altruistic user to the equilibrium utility he would have received in Nash equilibrium if he were selfish. We show by example that the VoU, in a game with nonlinear latency functions and atomic players, can be arbitrarily large. Since the Nash equilibrium social welfare of this example is arbitrarily far from social optimum, this example also has a Price of Anarchy (PoA) that is unbounded. The example is driven by there being a small number of players since the same example with non-atomic players yields a Nash equilibrium that is fully efficient.


Multi-channel Hybrid Access Femtocells: A Stochastic Geometric Analysis

Abstract: For two-tier networks consisting of macrocells and femtocells, the channel access mechanism can be configured to be open access, closed access, or hybrid access. Hybrid access arises as a compromise between open and closed access mechanisms, in which a fraction of available spectrum resource is shared to nonsubscribers while the remaining reserved for subscribers. This paper focuses on a hybrid access mechanism for multi-channel femtocells which employ orthogonal spectrum access schemes. Considering a randomized channel assignment strategy, we analyze the performance in the downlink. Using stochastic geometry as technical tools, we model the distribution of femtocells as Poisson point process or Neyman-Scott cluster process and derive the distributions of signal-to-interference-plus-noise ratios, and mean achievable rates, of both nonsubscribers and subscribers. The established expressions are amenable to numerical evaluation, and shed key insights into the performance tradeoff between subscribers and nonsubscribers. The analytical results are corroborated by numerical simulations.


Solving Detachability Problem for the Polynomial Ring by Signature-based Groebner Basis Algorithms

Abstract: Signature-based algorithms are a popular kind of algorithms for computing Groebner basis, including the famous F5 algorithm, F5C, extended F5, G2V and the GVW algorithm. In this paper, an efficient method is proposed to solve the detachability problem. The new method only uses the outputs of signature-based algorithms, and no extra Groebner basis computations are needed. When a Groebner basis is obtained by signature-based algorithms, the detachability problem can be settled in polynomial time.


A Key Establishment Scheme for Mobile Wireless Sensor Networks Using Post-Deployment Knowledge

Abstract: Establishment of pairwise keys between sensor nodes in a sensor network is a difficult problem due to resource limitations of sensor nodes as well as vulnerability to physical captures of sensor nodes by the enemy. Public-key cryptosystems are not much suited for most resource-constrained sensor networks. Recently, elliptic curve cryptographic techniques show that public key cryptosystem is also feasible for resource-constrained sensor networks. However, most researchers accept that the symmetric key cryptosystems are viable options for resource-constrained sensor networks. In this paper, we first develop a basic principle to address the key pre-distribution problem in mobile sensor networks. Then, using this developed basic principle, we propose a scheme which takes the advantage of the post-deployment knowledge. Our scheme is a modified version of the key prioritization technique proposed by Liu and Ning. Our improved scheme provides reasonable network connectivity and security. Moreover, the proposed scheme works for any deployment topology.


Security Model For Service-Oriented Architecture

Abstract: In this article, we examine how security applies to Service Oriented Architecture (SOA). Before we discuss security for SOA, lets take a step back and examine what SOA is. SOA is an architectural approach which involves applications being exposed as "services". Originally, services in SOA were associated with a stack of technologies which included SOAP, WSDL, and UDDI. This article addresses the defects of traditional enterprise application integration by combining service oriented-architecture and web service technology. Application integration is then simplified to development and integration of services to tackle connectivity of isomerous enterprise application integration, security, loose coupling between systems and process refactoring and optimization.


Accurate location estimation of moving object with energy constraint & adaptive update algorithms to save data

Abstract: In research paper "Accurate estimation of the target location of object with energy constraint & Adaptive Update Algorithms to Save Data" one of the central issues in sensor networks is track the location, of moving object which have overhead of saving data, an accurate estimation of the target location of object with energy constraint .We do not have any mechanism which control and maintain data .The wireless communication bandwidth is also very limited. Some field which is using this technique are flood and typhoon detection, forest fire detection, temperature and humidity and ones we have these information use these information back to a central air conditioning and ventilation system. In this research paper, we propose protocol based on the prediction and adaptive based algorithm which is using less sensor node reduced by an accurate estimation of the target location. we are using minimum three sensor node to get the accurate position .We can extend it upto four or five to find more accurate location but we have energy constraint so we are using three with accurate estimation of location help us to reduce sensor node..We show that our tracking method performs well in terms of energy saving regardless of mobility pattern of the mobile target .We extends the life time of network with less sensor node. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object. The agent is mobile since it will choose the sensor closest to the object to stay. The agent may invite some nearby slave sensors to cooperatively position the object and inhibit other irrelevant (i.e., farther) sensors from tracking the object. As a result, the communication and sensing overheads are greatly reduced.


Secure and Robust IPV6 Autoconfiguration Protocol For Mobile Adhoc Networks Under Strong Adversarial Model

Abstract: Automatic IP address assignment in Mobile Ad hoc Networks (MANETs) enables nodes to obtain routable addresses without any infrastructure. Different protocols have been developed throughout the last years to achieve this service. However, research primarily focused on correctness, efficiency and scalability; much less attention has been given to the security issues. The lack of security in the design of such protocols opens the possibility of many real threats leading to serious attacks in potentially hostile environments. Recently, few schemes have been proposed to solve this problem, but none of them has brought satisfactory solutions. Auto-configuration security issues are still an open problem. In this paper, a robust and secure stateful IP address allocation protocol for standalone MANETs is specified and evaluated within NS2. Our solution is based on mutual authentication, and a fully distributed Autoconfiguration and CA model, in conjunction with threshold cryptography. By deploying a new concept of joint IP address and public key certificate, we show that, instead of earlier approaches, our solution solves the problem of all possible attacks associated with dynamic IP address assignment in MANETs. The resulting protocol incurs low latency and control overhead


Two-stage coordination multi-radio multi-channel mac protocol for wireless mesh networks

Abstract: Within the wireless mesh network, a bottleneck problem arises as the number of concurrent traffic flows (NCTF) increases over a single common control channel, as it is for most conventional networks. To alleviate this problem, this paper proposes a two-stage coordination multi-radio multi-channel MAC (TSC-M2MAC) protocol that designates all available channels as both control channels and data channels in a time division manner through a two-stage coordination. At the first stage, a load balancing breadth-first-search-based vertex coloring algorithm for multi-radio conflict graph is proposed to intelligently allocate multiple control channels. At the second stage, a REQ/ACK/RES mechanism is proposed to realize dynamical channel allocation for data transmission. At this stage, the Channel-and-Radio Utilization Structure (CRUS) maintained by each node is able to alleviate the hidden nodes problem; also, the proposed adaptive adjustment algorithm for the Channel Negotiation and Allocation (CNA) sub-interval is able to cope with the variation of NCTF. In addition, we design a power saving mechanism for the TSC-M2MAC to decrease its energy consumption. Simulation results show that the proposed protocol is able to achieve higher throughput and lower end-to-end packet delay than conventional schemes. They also show that the TSC-M2MAC can achieve load balancing, save energy, and remain stable when the network becomes saturated.


Green: Towards a Pollution-Free Peer-to-Peer Content Sharing Service

Abstract: Peer-to-Peer (P2P) content sharing systems are susceptible to the content pollution attack, in which attackers aggressively inject polluted contents into the systems to reduce the availability of authentic contents, thus decreasing the confidence of participating users. In this paper, we design a pollution-free P2P content sharing system, Green, by exploiting the inherent content-based information and the social-based reputation. In Green, a content provider (i.e., creator or sharer) publishes the information of his shared contents to a group of content maintainers self-organized in a security overlay for providing the mechanisms of redundancy and reliability, so that a content requestor can obtain and filter the information of his requested content from the associated maintainers. We employ a reputation model to help the requestor better identify the polluted contents, and then utilize the social (friend-related) information to enhance the effectiveness and efficiency of our reputation model. Now, the requestor could easily select an authentic content version for downloading. While downloading, each requestor performs a realtime integrity verification and takes prompt protection to handle the content pollution. To further improve the system performance, we devise a scalable probabilistic verification scheme. Green is broadly applicable for both structured and unstructured overlay applications, and moreover, it is able to defeat various kinds of content pollution attacks without incurring significant overhead on the participating users. The evaluation in massive-scale networks validates the success of Green against the content pollution.


Architecture Of A Identity Based Firewall System

Abstract: Classic firewall systems are built to filter traffic based on IP addresses, source and destination ports and protocol types. The modern networks have grown to a level where the possibility for users' mobility is a must. In such networks, modern firewalls may introduce such complexity where administration can become very frustrating since it needs the intervention of a firewall administrator. The solution for this problem is an identity based firewall system. In this paper we will present a new design of a firewall system that uses the user's identity to filter the traffic. In the design phase we will define key points which have to be satisfied as a crucial milestone for the functioning of the whole Identity based firewall system.


Phagocytes: A Holistic Defense and Protection Against Active P2P Worms

Abstract: Active Peer-to-Peer (P2P) worms present serious threats to the global Internet by exploiting popular P2P applications to perform rapid topological self-propagation. Active P2P worms pose more deadly threats than normal scanning worms because they do not exhibit easily detectable anomalies, thus many existing defenses are no longer effective. We propose an immunity system with Phagocytes --- a small subset of elected P2P hosts that are immune with high probability and specialized in finding and "eating" worms in the P2P overlay. The Phagocytes will monitor their managed P2P hosts' connection patterns and traffic volume in an attempt to detect active P2P worm attacks. Once detected, local isolation, alert propagation and software patching will take place for containment. The Phagocytes further provide the access control and filtering mechanisms for communication establishment between the internal P2P overlay and the external hosts. We design a novel adaptive and interaction-based computational puzzle scheme at the Phagocytes to restrain external worms attacking the P2P overlay, without influencing legitimate hosts' experiences significantly. We implement a prototype system, and evaluate its performance based on realistic massive-scale P2P network traces. The evaluation results illustrate that our Phagocytes are capable of achieving a total defense against active P2P worms.


Fast k-means algorithm clustering

Abstract: k-means has recently been recognized as one of the best algorithms for clustering unsupervised data. Since k-means depends mainly on distance calculation between all data points and the centers, the time cost will be high when the size of the dataset is large (for example more than 500millions of points). We propose a two stage algorithm to reduce the time cost of distance calculation for huge datasets. The first stage is a fast distance calculation using only a small portion of the data to produce the best possible location of the centers. The second stage is a slow distance calculation in which the initial centers used are taken from the first stage. The fast and slow stages represent the speed of the movement of the centers. In the slow stage, the whole dataset can be used to get the exact location of the centers. The time cost of the distance calculation for the fast stage is very low due to the small size of the training data chosen. The time cost of the distance calculation for the slow stage is also minimized due to small number of iterations. Different initial locations of the clusters have been used during the test of the proposed algorithms. For large datasets, experiments show that the 2-stage clustering method achieves better speed-up (1-9 times).


Program slicing techniques and its applications

Abstract: Program understanding is an important aspect in Software Maintenance and Reengineering. Understanding the program is related to execution behaviour and relationship of variable involved in the program. The task of finding all statements in a program that directly or indirectly influence the value for an occurrence of a variable gives the set of statements that can affect the value of a variable at some point in a program is called a program slice. Program slicing is a technique for extracting parts of computer programs by tracing the programs' control and data flow related to some data item. This technique is applicable in various areas such as debugging, program comprehension and understanding, program integration, cohesion measurement, re-engineering, maintenance, testing where it is useful to be able to focus on relevant parts of large programs. This paper focuses on the various slicing techniques (not limited to) like static slicing, quasi static slicing, dynamic slicing and conditional slicing. This paper also includes various methods in performing the slicing like forward slicing, backward slicing, syntactic slicing and semantic slicing. The slicing of a program is carried out using Java which is a object oriented programming language.


Real time face recognition using adaboost improved fast PCA algorithm

Abstract: This paper presents an automated system for human face recognition in a real time background world for a large homemade dataset of persons face. The task is very difficult as the real time background subtraction in an image is still a challenge. Addition to this there is a huge variation in human face image in terms of size, pose and expression. The system proposed collapses most of this variance. To detect real time human face AdaBoost with Haar cascade is used and a simple fast PCA and LDA is used to recognize the faces detected. The matched face is then used to mark attendance in the laboratory, in our case. This biometric system is a real time attendance system based on the human face recognition with a simple and fast algorithms and gaining a high accuracy rate..


Variability of location management costs with different mobilities and timer periods to update locations

Abstract: In this article, we examine the Location Management costs in mobile communication networks utilizing the timer-based method. From the study of the probabilities that a mobile terminal changes a number of Location Areas between two calls, we identify a threshold value of 0.7 for the Call-to-Mobility Ratio (CMR) below which the application of the timer-based method is most appropriate. We characterize the valley appearing in the evolution of the costs with the timeout period, showing that the time interval required to reach 90% of the stabilized costs grows with the mobility index, the paging cost per Location Area and the movement dimension, in opposition to the behavior presented by the time interval that achieves the minimum of the costs. The results obtained for CMRs below the suggested 0.7 threshold show that the valley appearing in the costs tends to disappear for CMRs within [0.001, 0.7] in onedimensional movements and within [0.2, 0.7] in two-dimensional ones, and when the normalized paging cost per Location Area is below 0.3.


Savings in location management costs leveraging user statistics

Abstract: The growth in the number of users in mobile communications networks and the rise in the traffic generated by each user, are responsible for the increasing importance of Mobility Management. Within Mobility Management, the main objective of Location Management is to enable the roaming of the user in the coverage area. In this paper, we analyze the savings in Location Management costs obtained leveraging the users' statistics, in comparison with the classical strategy. In particular, we introduce two novel algorithms to obtain the Beta parameters (useful terms in the calculation of location update costs for different Location Management strategies), utilizing a geographical study of relative positions of the cells within the location areas. Eventually, we discuss the influence of the different network parameters on the total Location Management costs savings for both the radio interface and the fixed network part, providing useful guidelines for the optimum design of the networks.


Sparsity without the Complexity: Loss Localisation using Tree Measurements

Abstract: We study network loss tomography based on observing average loss rates over a set of paths forming a tree -- a severely underdetermined linear problem for the unknown link loss probabilities. We examine in detail the role of sparsity as a regularising principle, pointing out that the problem is technically distinct from others in the compressed sensing literature. While sparsity has been applied in the context of tomography, key questions regarding uniqueness and recovery remain unanswered. Our work exploits the tree structure of path measurements to derive sufficient conditions for sparse solutions to be unique and the condition that $\ell_1$ minimization recovers the true underlying solution. We present a fast single-pass linear algorithm for $\ell_1$ minimization and prove that a minimum $\ell_1$ solution is both unique and sparsest for tree topologies. By considering the placement of lossy links within trees, we show that sparse solutions remain unique more often than is commonly supposed. We prove similar results for a noisy version of the problem.


An Efficient Architecture for Information Retrieval in P2P Context Using Hypergraph

Abstract: Peer-to-peer (P2P) Data-sharing systems now generate a significant portion of Internet traffic. P2P systems have emerged as an accepted way to share enormous volumes of data. Needs for widely distributed information systems supporting virtual organizations have given rise to a new category of P2P systems called schema-based. In such systems each peer is a database management system in itself, ex-posing its own schema. In such a setting, the main objective is the efficient search across peer databases by processing each incoming query without overly consuming bandwidth. The usability of these systems depends on successful techniques to find and retrieve data; however, efficient and effective routing of content-based queries is an emerging problem in P2P networks. This work was attended as an attempt to motivate the use of mining algorithms in the P2P context may improve the significantly the efficiency of such methods. Our proposed method based respectively on combination of clustering with hypergraphs. We use ECCLAT to build approximate clustering and discovering meaningful clusters with slight overlapping. We use an algorithm MTMINER to extract all minimal transversals of a hypergraph (clusters) for query routing. The set of clusters improves the robustness in queries routing mechanism and scalability in P2P Network. We compare the performance of our method with the baseline one considering the queries routing problem. Our experimental results prove that our proposed methods generate impressive levels of performance and scalability with with respect to important criteria such as response time, precision and recall.


A Novel Header Matching Algorithm for Intrusion Detection Systems

Abstract: The evolving necessity of the Internet increases the demand on the bandwidth. Therefore, this demand opens the doors for the hackers' community to develop new methods and techniques to gain control over networking systems. Hence, the intrusion detection systems (IDS) are insufficient to prevent/detect unauthorized access the network. Network Intrusion Detection System (NIDS) is one example that still suffers from performance degradation due the increase of the link speed in today's networks. In This paper we proposed a novel algorithm to detect the intruders, who's trying to gain access to the network using the packets header parameters such as; source/destination address, source/destination port, and protocol without the need to inspect each packet content looking for signatures/patterns. However, the "Packet Header Matching" algorithm enhances the overall speed of the matching process between the incoming packet headers against the rule set. We ran the proposed algorithm to proof the proposed concept in coping with the traffic arrival speeds and the various bandwidth demands. The achieved results were of significant enhancement of the overall performance in terms of detection speed.


A Driven Backup Routing Table to Find Alternative Dijoint Path in Ad Hoc Wireless

Abstract: The performances of the routing protocols are important since they compute the primary path between source and destination. In addition, routing protocols need to detect failure within a short period of time when nodes move to start updating the routing table in order to find a new primary path to the destination. Meantime, loss of packets and end-to- end delays will increase thereby reducing throughput and degrading the performance of the network. This paper proposes a new algorithm, DBRT (Driven Backup Routing Table), to improve the existing proactive protocols such as DSDV (Destination Sequenced Distance Vector) protocol by creating a backup routing table to provide multiple alternative routes. The DBRT algorithm identifies adjacent nodes for each node in the same range and then selects one of these as a backup next hop according to the available path to the destination. The results show that loss of data packets, throughput and end-to-end delay times between source and destination are improved. The results show that the new protocol does not degrade the network's performance despite sending extra messages to construct and update the new backup routing table. Simulations (using an NS2 simulator) are undertaken to demonstrate the difference between using a DSDV protocol with or without the proposed schema.


Efficient Algorithms to Enhance Recovery Schema in Link State Protocols

Abstract: With the increasing demands for real-time applications traffic in net- works such as video and voice a high convergence time for the existing routing protocols when failure occurred is required. These applications can be very sensitive to packet loss when link/node goes down. In this paper, we propose two algorithms schemas for the link state protocol to reroute the traffic in two states; first, pre-calculated an alternative and disjoint path with the primary one from the source to the destination by re-routing traffic through it, regardless of the locations of failure and the number of failed links. Second, rerouting the traffic via an alternative path from a node whose local link is down without the need to wait until the source node knows about the failure. This is achieved by creating a new backup routing table based on the original routing table which is computed by the dijkstra algorithm. The goal of these algorithms is to reduce loss of packets, end-to-end delay time, improve throughput and avoiding local loop when nodes re-converge the topology in case of failure.


A Novel Approach for Authenticating Textual or Graphical Passwords Using Hopfield Neural Network

Abstract: Password authentication using Hopfield Networks is presented in this paper. In this paper we discussed the Hopfield Network Scheme for Textual and graphical passwords, for which input Password will be converted in to probabilistic values. We observed how to get password authentication using Probabilistic values for Textual passwords and Graphical passwords. This study proposes the use of a Hopfield neural network technique for password authentication. In comparison to existing layered neural network techniques, the proposed method provides better accuracy and quicker response time to registration and password changes.


Impact of Software Requirement Volatility Pattern on Project Dynamics: Evidences from a Case Study

Abstract: Requirements are found to change in various ways during the course of a project. This can affect the process in widely different manner and extent. Here we present a case study where-in we investigate the impact of requirement volatility pattern on project performance. The project setting described in the case is emulated on a validated system dynamics model representing the waterfall model. The findings indicate deviations in project outcome from the estimated thereby corroborating to previous findings. The results reinforce the applicability of system dynamics approach to analyze project performance under requirement volatility, which is expected to speed up adoption of the same in organizations and in the process contribute to more project successes.


Proceedings First International Workshop on Process Algebra and Coordination

Abstract: Process algebra provides abstract and rigorous means for studying communicating concurrent systems. Coordination languages also provide abstract means for the specifying and programming communication of components. Hence, the two fields seem to have very much in common and the link between these two research areas have been established formally by means of several translations, mainly from coordination languages to process algebras. There have also been proposals of process algebras whose communication policy is inspired by the one underlying coordination languages. The aim of this workshop was to push the state of the art in the study of the connections between process algebra and coordination languages by bringing together experts as well as young researchers from the two fields to communicate their ideas and findings. It includes both contributed and invited papers that have been presented during the one day meeting on Process Algebra and Coordination (PACO 2011) which took place on June 9, 2011 in Reykjavik, Iceland.


Non-cooperative Game For Capacity Offload

Abstract: With the blasting increase of wireless data traffic, incumbent wireless service providers (WSPs) face critical challenges in provisioning spectrum resource. Given the permission of unlicensed access to TV white spaces, WSPs can alleviate their burden by exploiting the concept of "capacity offload" to transfer part of their traffic load to unlicensed spectrum. For such use cases, a central problem is for WSPs to coexist with others, since all of them may access the unlicensed spectrum without coordination thus interfering each other. Game theory provides tools for predicting the behavior of WSPs, and we formulate the coexistence problem under the framework of non-cooperative games as a capacity offload game (COG). We show that a COG always possesses at least one pure-strategy Nash equilibrium (NE), and does not have any mixed-strategy NE. The analysis provides a full characterization of the structure of the NEs in two-player COGs. When the game is played repeatedly and each WSP individually updates its strategy based on its best-response function, the resulting process forms a best-response dynamic. We establish that, for two-player COGs, alternating-move best-response dynamics always converge to an NE, while simultaneous-move best-response dynamics does not always converge to an NE when multiple NEs exist. When there are more than two players in a COG, if the network configuration satisfies certain conditions so that the resulting best-response dynamics become linear, both simultaneous-move and alternating-move best-response dynamics are guaranteed to converge to the unique NE.


Understanding need of "Uncertainty Analysis" in the system Design process

Abstract: Software project development process is requiring accurate software cost and schedule estimation for achieve goal or success. A lot it referred to as the "Intricate brainteaser" because of its conscience attribute which is impact by complexity and uncertainty, Generally estimation is not as difficult or puzzling as people think. In fact, generating accurate estimates is straightforward-once you understand the intensity of uncertainty and module which contribute itself process. In our everyday life, we enhance our estimation based on past experience in which problem solve by which method and in which condition and which opportune provide that method to produce better result . So, Instead of unexplained treatises and inflexible modeling techniques, this will guide highlights a proven set of procedures, understandable formulas, and heuristics that individuals and complete team can apply to their projects to help achieve estimation ability with choose appropriate development approaches In the early stage of software life cycle project manager are inefficient to estimate the effort, schedule, cost estimation and its development approach .This in turn, confuses the manager to bid effectively on software project and choose incorrect development approach. That will directly effect on productivity cycle and increase level of uncertainty. This becomes a strong cause of project failure. So to avoid such problem if we know level and sources of uncertainty in model design, It will directive the developer to design accurate software cost and schedule estimation. which are require l for software project success. This paper demonstrates need of uncertainty analysis module at the modeling process for assist to recognize modular uncertainty system development process and the role of uncertainty at different stages in the modeling


On a New Multicomputer Interconnection Topology for Massively Parallel Systems

Abstract: This paper introduces a new interconnection network topology called Balanced Varietal Hypercube (BVH), suitable for massively parallel systems. The proposed topology being a hybrid structure retains almost all the attractive properties of Balanced Hypercube and Varietal Hypercube. The topology, various parameters, routing and broadcasting of Balanced Varietal Hypercube are presented. The performance of the Balanced Varietal Hypercube is compared with other networks. In terms of diameter, cost and average distance and reliability the proposed network is found to be better than the Hypercube, Balanced Hypercube and Varietal Hypercube. Also it is more reliable and cost-effective than Hypercube and Balanced Hypercube.


Cutaneous Force Feedback as a Sensory Subtraction Technique in Haptics

Abstract: A novel sensory substitution technique is presented. Kinesthetic and cutaneous force feedback are substituted by cutaneous feedback (CF) only, provided by two wearable devices able to apply forces to the index finger and the thumb, while holding a handle during a teleoperation task. The force pattern, fed back to the user while using the cutaneous devices, is similar, in terms of intensity and area of application, to the cutaneous force pattern applied to the finger pad while interacting with a haptic device providing both cutaneous and kinesthetic force feedback. The pattern generated using the cutaneous devices can be thought as a subtraction between the complete haptic feedback (HF) and the kinesthetic part of it. For this reason, we refer to this approach as sensory subtraction instead of sensory substitution. A needle insertion scenario is considered to validate the approach. The haptic device is connected to a virtual environment simulating a needle insertion task. Experiments show that the perception of inserting a needle using the cutaneous-only force feedback is nearly indistinguishable from the one felt by the user while using both cutaneous and kinesthetic feedback. As most of the sensory substitution approaches, the proposed sensory subtraction technique also has the advantage of not suffering from stability issues of teleoperation systems due, for instance, to communication delays. Moreover, experiments show that the sensory subtraction technique outperforms sensory substitution with more conventional visual feedback (VF).