A Matrix Hyperbolic Cosine Algorithm and Applications

Abstract: In this paper, we generalize Spencer's hyperbolic cosine algorithm to the matrix-valued setting. We apply the proposed algorithm to several problems by analyzing its computational efficiency under two special cases of matrices; one in which the matrices have a group structure and an other in which they have rank-one. As an application of the former case, we present a deterministic algorithm that, given the multiplication table of a finite group of size $n$, it constructs an expanding Cayley graph of logarithmic degree in near-optimal O(n^2 log^3 n) time. For the latter case, we present a fast deterministic algorithm for spectral sparsification of positive semi-definite matrices, which implies an improved deterministic algorithm for spectral graph sparsification of dense graphs. In addition, we give an elementary connection between spectral sparsification of positive semi-definite matrices and element-wise matrix sparsification. As a consequence, we obtain improved element-wise sparsification algorithms for diagonally dominant-like matrices.


On Computational Power of Quantum Read-Once Branching Programs

Abstract: In this paper we review our current results concerning the computational power of quantum read-once branching programs. First of all, based on the circuit presentation of quantum branching programs and our variant of quantum fingerprinting technique, we show that any Boolean function with linear polynomial presentation can be computed by a quantum read-once branching program using a relatively small (usually logarithmic in the size of input) number of qubits. Then we show that the described class of Boolean functions is closed under the polynomial projections.


Autotagging music with conditional restricted Boltzmann machines

Abstract: This paper describes two applications of conditional restricted Boltzmann machines (CRBMs) to the task of autotagging music. The first consists of training a CRBM to predict tags that a user would apply to a clip of a song based on tags already applied by other users. By learning the relationships between tags, this model is able to pre-process training data to significantly improve the performance of a support vector machine (SVM) autotagging. The second is the use of a discriminative RBM, a type of CRBM, to autotag music. By simultaneously exploiting the relationships among tags and between tags and audio-based features, this model is able to significantly outperform SVMs, logistic regression, and multi-layer perceptrons. In order to be applied to this problem, the discriminative RBM was generalized to the multi-label setting and four different learning algorithms for it were evaluated, the first such in-depth analysis of which we are aware.


Functor is to Lens as Applicative is to Biplate: Introducing Multiplate

Abstract: This paper gives two new categorical characterisations of lenses: one as a coalgebra of the store comonad, and the other as a monoidal natural transformation on a category of a certain class of coalgebras. The store comonad of the first characterisation can be generalized to a Cartesian store comonad, and the coalgebras of this Cartesian store comonad turn out to be exactly the Biplates of the Uniplate generic programming library. On the other hand, the monoidal natural transformations on functors can be generalized to work on a category of more specific coalgebras. This generalization turns out to be the type of compos from the Compos generic programming library. A theorem, originally conjectured by van Laarhoven, proves that these two generalizations are isomorphic, thus the core data types of the Uniplate and Compos libraries supporting generic program on single recursive types are the same. Both the Uniplate and Compos libraries generalize this core functionality to support mutually recursive types in different ways. This paper proposes a third extension to support mutually recursive data types that is as powerful as Compos and as easy to use as Uniplate. This proposal, called Multiplate, only requires rank 3 polymorphism in addition to the normal type class mechanism of Haskell.


Polynomial Weights or Generalized Geometric Weights: Yet Another Scheme for Assigning Credits to Multiple Authors

Abstract: Devising a weight assignment policy for assigning credits to multiple authors of a manuscript is a challenging task. In this paper, we present a scheme for assigning credits to multiple authors that we call a polynomial weight assignment scheme. We compare our scheme with other schemes proposed in the literature.


Computing the Fr\'{e}chet Distance Between Folded Polygons

Abstract: Computing the Fr\'{e}chet distance for surfaces is a surprisingly hard problem and the only known algorithm is limited to computing it between flat surfaces. We adapt this algorithm to create one for computing the Fr\'{e}chet distance for a class of non-flat surfaces which we call folded polygons. Unfortunately, the original algorithm cannot be extended directly. We present three different methods to adapt it. The first of which is a fixed-parameter tractable algorithm. The second is a polynomial-time approximation algorithm. Finally, we present a restricted class of folded polygons for which we can compute the Fr\'{e}chet distance in polynomial time.


Predicting User Preferences

Abstract: The many metrics employed for the evaluation of search engine results have not themselves been conclusively evaluated. We propose a new measure for a metric's ability to identify user preference of result lists. Using this measure, we evaluate the metrics Discounted Cumulated Gain, Mean Average Precision and classical precision, finding that the former performs best. We also show that considering more results for a given query can impair rather than improve a metric's ability to predict user preferences.


A new ANEW: Evaluation of a word list for sentiment analysis in microblogs

Abstract: Sentiment analysis of microblogs such as Twitter has recently gained a fair amount of attention. One of the simplest sentiment analysis approaches compares the words of a posting against a labeled word list, where each word has been scored for valence, -- a 'sentiment lexicon' or 'affective word lists'. There exist several affective word lists, e.g., ANEW (Affective Norms for English Words) developed before the advent of microblogging and sentiment analysis. I wanted to examine how well ANEW and other word lists performs for the detection of sentiment strength in microblog posts in comparison with a new word list specifically constructed for microblogs. I used manually labeled postings from Twitter scored for sentiment. Using a simple word matching I show that the new word list may perform better than ANEW, though not as good as the more elaborate approach found in SentiStrength.


A Characterization of all Stable Minimal Separator Graphs

Abstract: In this paper, our goal is to characterize two graph classes based on the properties of minimal vertex (edge) separators. We first present a structural characterization of graphs in which every minimal vertex separator is a stable set. We show that such graphs are precisely those in which the induced subgraph, namely, a cycle with exactly one chord is forbidden. We also show that deciding maximum such forbidden subgraph is NP-complete by establishing a polynomial time reduction from maximum induced cycle problem [1]. This result is of independent interest and can be used in other combinatorial problems. Secondly, we prove that a graph has the following property: every minimal edge separator induces a matching (that is no two edges share a vertex in common) if and only if it is a tree.


Fitting Ranked English and Spanish Letter Frequency Distribution in U.S. and Mexican Presidential Speeches

Abstract: The limited range in its abscissa of ranked letter frequency distributions causes multiple functions to fit the observed distribution reasonably well. In order to critically compare various functions, we apply the statistical model selections on ten functions, using the texts of U.S. and Mexican presidential speeches in the last 1-2 centuries. Dispite minor switching of ranking order of certain letters during the temporal evolution for both datasets, the letter usage is generally stable. The best fitting function, judged by either least-square-error or by AIC/BIC model selection, is the Cocho/Beta function. We also use a novel method to discover clusters of letters by their observed-over-expected frequency ratios.


Syntactic Complexity of Prefix-, Suffix-, Bifix-, and Factor-Free Regular Languages

Abstract: The syntactic complexity of a regular language is the cardinality of its syntactic semigroup. The syntactic complexity of a subclass of the class of regular languages is the maximal syntactic complexity of languages in that class, taken as a function of the state complexity $n$ of these languages. We study the syntactic complexity of prefix-, suffix-, bifix-, and factor-free regular languages. We prove that $n^{n-2}$ is a tight upper bound for prefix-free regular languages. We present properties of the syntactic semigroups of suffix-, bifix-, and factor-free regular languages, conjecture tight upper bounds on their size to be $(n-1)^{n-2}+(n-2)$, $(n-1)^{n-3} + (n-2)^{n-3} + (n-3)2^{n-3}$, and $(n-1)^{n-3} + (n-3)2^{n-3} + 1$, respectively, and exhibit languages with these syntactic complexities.


A study of the existing linear algebra libraries that you can use from C++ (Une \'etude des biblioth\`eques d'alg\`ebre lin\'eaire utilisables en C++)


A study of the existing libraries to read from configuration files (from C++)


Generalized Filtering Decomposition

Abstract: This paper introduces a new preconditioning technique that is suitable for matrices arising from the discretization of a system of PDEs on unstructured grids. The preconditioner satisfies a so-called filtering property, which ensures that the input matrix is identical with the preconditioner on a given filtering vector. This vector is chosen to alleviate the effect of low frequency modes on convergence and so decrease or eliminate the plateau which is often observed in the convergence of iterative methods. In particular, the paper presents a general approach that allows to ensure that the filtering condition is satisfied in a matrix decomposition. The input matrix can have an arbitrary sparse structure. Hence, it can be reordered using nested dissection, to allow a parallel computation of the preconditioner and of the iterative process.


Connectivity Damage to a Graph by the Removal of an Edge or a Vertex

Abstract: The approach of quantifying the damage inflicted on a graph in Albert, Jeong and Barabsi's (AJB) report "Error and Attack Tolerance of Complex Networks" using the size of the largest connected component and the average size of the remaining components does not capture our intuitive idea of the damage to a graph caused by disconnections. We evaluate an alternative metric based on average inverse path lengths (AIPLs) that better fits our intuition that a graph can still be reasonably functional even when it is disconnected. We compare our metric with AJB's using a test set of graphs and report the differences. AJB's report should not be confused with a report by Crucitti et al. with the same name. Based on our analysis of graphs of different sizes and types, and using various numerical and statistical tools; the ratio of the average inverse path lengths of a connected graph of the same size as the sum of the size of the fragments of the disconnected graph can be used as a metric about the damage of a graph by the removal of an edge or a node. This damage is reported in the range (0,1) where 0 means that the removal had no effect on the graph's capability to perform its functions. A 1 means that the graph is totally dysfunctional. We exercise our metric on a collection of sample graphs that have been subjected to various attack profiles that focus on edge, node or degree betweenness values. We believe that this metric can be used to quantify the damage done to the graph by an attacker, and that it can be used in evaluating the positive effect of adding additional edges to an existing graph.


Human-Assisted Graph Search: It's Okay to Ask Questions

Abstract: We consider the problem of human-assisted graph search: given a directed acyclic graph with some (unknown) target node(s), we consider the problem of finding the target node(s) by asking an omniscient human questions of the form "Is there a target node that is reachable from the current node?". This general problem has applications in many domains that can utilize human intelligence, including curation of hierarchies, debugging workflows, image segmentation and categorization, interactive search and filter synthesis. To our knowledge, this work provides the first formal algorithmic study of the optimization of human computation for this problem. We study various dimensions of the problem space, providing algorithms and complexity results. Our framework and algorithms can be used in the design of an optimizer for crowd-sourcing platforms such as Mechanical Turk.


Guided Data Repair

Abstract: In this paper we present GDR, a Guided Data Repair framework that incorporates user feedback in the cleaning process to enhance and accelerate existing automatic repair techniques while minimizing user involvement. GDR consults the user on the updates that are most likely to be beneficial in improving data quality. GDR also uses machine learning methods to identify and apply the correct updates directly to the database without the actual involvement of the user on these specific updates. To rank potential updates for consultation by the user, we first group these repairs and quantify the utility of each group using the decision-theory concept of value of information (VOI). We then apply active learning to order updates within a group based on their ability to improve the learned model. User feedback is used to repair the database and to adaptively refine the training set for the model. We empirically evaluate GDR on a real-world dataset and show significant improvement in data quality using our user guided repairing process. We also, assess the trade-off between the user efforts and the resulting data quality.


High-Throughput Transaction Executions on Graphics Processors

Abstract: OLTP (On-Line Transaction Processing) is an important business system sector in various traditional and emerging online services. Due to the increasing number of users, OLTP systems require high throughput for executing tens of thousands of transactions in a short time period. Encouraged by the recent success of GPGPU (General-Purpose computation on Graphics Processors), we propose GPUTx, an OLTP engine performing high-throughput transaction executions on the GPU for in-memory databases. Compared with existing GPGPU studies usually optimizing a single task, transaction executions require handling many small tasks concurrently. Specifically, we propose the bulk execution model to group multiple transactions into a bulk and to execute the bulk on the GPU as a single task. The transactions within the bulk are executed concurrently on the GPU. We study three basic execution strategies (one with locks and the other two lock-free), and optimize them with the GPU features including the hardware support of atomic operations, the massive thread parallelism and the SPMD (Single Program Multiple Data) execution. We evaluate GPUTx on a recent NVIDIA GPU in comparison with its counterpart on a quad-core CPU. Our experimental results show that optimizations on GPUTx significantly improve the throughput, and the optimized GPUTx achieves 4-10 times higher throughput than its CPU-based counterpart on public transaction processing benchmarks.


Incrementally Maintaining Classification using an RDBMS

Abstract: The proliferation of imprecise data has motivated both researchers and the database industry to push statistical techniques into relational database management systems (RDBMSs). We study algorithms to maintain model-based views for a popular statistical technique, classification, inside an RDBMS in the presence of updates to the training examples. We make three technical contributions: (1) An algorithm that incrementally maintains classification inside an RDBMS. (2) An analysis of the above algorithm that shows that our algorithm is optimal among all deterministic algorithms (and asymptotically within a factor of 2 of a nondeterministic optimal). (3) An index structure based on the technical ideas that underlie the above algorithm which allows us to store only a fraction of the entities in memory. We apply our techniques to text processing, and we demonstrate that our algorithms provide several orders of magnitude improvement over non-incremental approaches to classification on a variety of data sets: such as the Cora, UCI Machine Learning Repository data sets, Citeseer, and DBLife.


Proceedings Types for Proofs and Programs, Revised Selected Papers

Abstract: Types for Proofs and Programs is the annual meeting of the Types Project, whose aim is to develop the technology of formal reasoning and computer programming based on Type Theory. This is done by improving the languages and computerised tools for reasoning, and by applying the technology in several domains such as analysis of programming languages, certified software, formalisation of mathematics and mathematics education. The 2009 meeting took place in Aussois, France, and we thank the invited speakers Richard Garner, Peter Hancock, Pawe{\l} Urzyczyn for excellent talks. The present volume consists of papers not necessarily presented at the workshop, selected by Thorsten Altenkirch, Tom Hirschowitz, Christophe Raffalli, and Alan Schmitt, with help from Matthieu Sozeau and Makarius Wenzel.


Fast $q$-gram Mining on SLP Compressed Strings

Abstract: We present simple and efficient algorithms for calculating $q$-gram frequencies on strings represented in compressed form, namely, as a straight line program (SLP). Given an SLP of size $n$ that represents string $T$, we present an $O(qn)$ time and space algorithm that computes the occurrence frequencies of $q$-grams in $T$. Computational experiments show that our algorithm and its variation are practical for small $q$, actually running faster on various real string data, compared to algorithms that work on the uncompressed text. We also discuss applications in data mining and classification of string data, for which our algorithms can be useful.


Reduced Ordered Binary Decision Diagram with Implied Literals: A New knowledge Compilation Approach

Abstract: Knowledge compilation is an approach to tackle the computational intractability of general reasoning problems. According to this approach, knowledge bases are converted off-line into a target compilation language which is tractable for on-line querying. Reduced ordered binary decision diagram (ROBDD) is one of the most influential target languages. We generalize ROBDD by associating some implied literals in each node and the new language is called reduced ordered binary decision diagram with implied literals (ROBDD-L). Then we discuss a kind of subsets of ROBDD-L called ROBDD-i with precisely i implied literals (0 \leq i \leq \infty). In particular, ROBDD-0 is isomorphic to ROBDD; ROBDD-\infty requires that each node should be associated by the implied literals as many as possible. We show that ROBDD-i has uniqueness over some specific variables order, and ROBDD-\infty is the most succinct subset in ROBDD-L and can meet most of the querying requirements involved in the knowledge compilation map. Finally, we propose an ROBDD-i compilation algorithm for any i and a ROBDD-\infty compilation algorithm. Based on them, we implement a ROBDD-L package called BDDjLu and then get some conclusions from preliminary experimental results: ROBDD-\infty is obviously smaller than ROBDD for all benchmarks; ROBDD-\infty is smaller than the d-DNNF the benchmarks whose compilation results are relatively small; it seems that it is better to transform ROBDDs-\infty into FBDDs and ROBDDs rather than straight compile the benchmarks.


Cryptanalysis And Further Improvement Of A Biometric-Based Remote User Authentication Scheme Using Smart Cards

Abstract: Recently, Li et al. proposed a secure biometric-based remote user authentication scheme using smart cards to withstand the security flaws of Li-Hwang's efficient biometric-based remote user authentication scheme using smart cards. Li et al.'s scheme is based on biometrics verification, smart card and one-way hash function, and it also uses the random nonce rather than a synchronized clock, and thus it is efficient in computational cost and more secure than Li-Hwang's scheme. Unfortunately, in this paper we show that Li et al.'s scheme still has some security weaknesses in their design. In order to withstand those weaknesses in their scheme, we further propose an improvement of their scheme so that the improved scheme always provides proper authentication and as a result, it establishes a session key between the user and the server at the end of successful user authentication.


A Longitudinal Study of Social Media Privacy Behavior

Abstract: Existing constructs for privacy concerns and behaviors do not adequately model deviations between user attitudes and behaviors. Although a number of studies have examined supposed deviations from rationality by online users, true explanations for these behaviors may lie in factors not previously addressed in privacy concern constructs. In particular, privacy attitudes and behavioral changes over time have not been examined within the context of an empirical study. This paper presents the results of an Agile, sprint-based longitudinal study of Social Media users conducted over a two year period between April of 2009 and March of 2011. This study combined concepts drawn from Privacy Regulation Theory with the constructs of the Internet Users' Information and Privacy Concern model to create a series of online surveys that examined changes of Social Media privacy attitudes and self-reported behaviors over time. The main findings of this study are that, over a two year period between 2009 and 2011, respondents' privacy concerns and distrust of Social Media Sites increased significantly, while their disclosure of personal information and willingness to connect with new online friends decreased significantly. Further qualitative interviews of selected respondents identified these changes as emblematic of users developing ad-hoc risk mitigation strategies to address privacy threats.


Using Soft Computer Techniques on Smart Devices for Monitoring Chronic Diseases: the CHRONIOUS case

Abstract: CHRONIOUS is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touchscreen) and a machine learning module. All these modules interact each other to allow the monitoring of two types of chronic diseases and to help clinician in taking decision for cure purpose. This paper illustrates how some machine learning algorithms and a rule based decision support system can be used in smart devices, to monitor chronic patient. We will analyse how a set of machine learning algorithms can be used in smart devices to alert the clinician in case of a patient health condition worsening trend.


Measuring NUMA effects with the STREAM benchmark

Abstract: Modern high-end machines feature multiple processor packages, each of which contains multiple independent cores and integrated memory controllers connected directly to dedicated physical RAM. These packages are connected via a shared bus, creating a system with a heterogeneous memory hierarchy. Since this shared bus has less bandwidth than the sum of the links to memory, aggregate memory bandwidth is higher when parallel threads all access memory local to their processor package than when they access memory attached to a remote package. But, the impact of this heterogeneous memory architecture is not easily understood from vendor benchmarks. Even where these measurements are available, they provide only best-case memory throughput. This work presents a series of modifications to the well-known STREAM benchmark to measure the effects of NUMA on both a 48-core AMD Opteron machine and a 32-core Intel Xeon machine.


Generic Trace Logics

Abstract: We combine previous work on coalgebraic logic with the coalgebraic traces semantics of Hasuo, Jacobs, and Sokolova.


Decentralized Constraint Satisfaction

Abstract: We show that several important resource allocation problems in wireless networks fit within the common framework of Constraint Satisfaction Problems (CSPs). Inspired by the requirements of these applications, where variables are located at distinct network devices that may not be able to communicate but may interfere, we define natural criteria that a CSP solver must possess in order to be practical. We term these algorithms decentralized CSP solvers. The best known CSP solvers were designed for centralized problems and do not meet these criteria. We introduce a stochastic decentralized CSP solver and prove that it will find a solution in almost surely finite time, should one exist, also showing it has many practically desirable properties. We benchmark the algorithm's performance on a well-studied class of CSPs, random k-SAT, illustrating that the time the algorithm takes to find a satisfying assignment is competitive with stochastic centralized solvers on problems with order a thousand variables despite its decentralized nature. We demonstrate the solver's practical utility for the problems that motivated its introduction by using it to find a non-interfering channel allocation for a network formed from data from downtown Manhattan.


Decoding square-free Goppa codes over $\F_p$

Abstract: We propose a new, efficient non-deterministic decoding algorithm for square-free Goppa codes over $\F_p$ for any prime $p$. If the code in question has degree $t$ and the average distance to the closest codeword is at least $(4/p)t + 1$, the proposed decoder can uniquely correct up to $(2/p)t$ errors with high probability. The correction capability is higher if the distribution of error magnitudes is not uniform, approaching or reaching $t$ errors when any particular error value occurs much more often than others or exclusively. This makes the method interesting for (semantically secure) cryptosystems based on the decoding problem for permuted and punctured Goppa codes.


A Light Weight Protocol to Provide Location Privacy in Wireless Body Area networks

Abstract: Location privacy is one of the major security problems in a Wireless Body Area Networks (WBANs). An eavesdropper can keep track of the place and time devices are communicating. To make things even worse, the attacker does not have to be physically close to the communicating devices, he can use a device with a stronger antenna. The unique hardware address of a mobile device can often be linked to the identity of the user operating the device. This represents a violation of the user's privacy. The user should decide when his/her location is revealed and when not. In this paper, we first categorize the type of eavesdroppers for WBANs, and then we propose a new scheme to provide the location privacy in Wireless Body Area Networks (WBANs).


Path coalitional games

Abstract: We present a general framework to model strategic aspects and stable and fair resource allocations in networks via variants and generalizations of path coalitional games. In these games, a coalition of edges or vertices is successful if it can enable an s-t path. We present polynomial-time algorithms to compute and verify least core payoffs of cost-based generalizations of path coalitional games and their duals, thereby settling a number of open problems. The least core payoffs of path coalitional games are completely characterized and a polynomial-time algorithm for computing the nucleolus of edge path coalitional games on undirected series-parallel graphs is presented.


Superposition as a logical glue

Abstract: The typical mathematical language systematically exploits notational and logical abuses whose resolution requires not just the knowledge of domain specific notation and conventions, but not trivial skills in the given mathematical discipline. A large part of this background knowledge is expressed in form of equalities and isomorphisms, allowing mathematicians to freely move between different incarnations of the same entity without even mentioning the transformation. Providing ITP-systems with similar capabilities seems to be a major way to improve their intelligence, and to ease the communication between the user and the machine. The present paper discusses our experience of integration of a superposition calculus within the Matita interactive prover, providing in particular a very flexible, "smart" application tactic, and a simple, innovative approach to automation.


Nonuniform Coercions via Unification Hints

Abstract: We introduce the notion of nonuniform coercion, which is the promotion of a value of one type to an enriched value of a different type via a nonuniform procedure. Nonuniform coercions are a generalization of the (uniform) coercions known in the literature and they arise naturally when formalizing mathematics in an higher order interactive theorem prover using convenient devices like canonical structures, type classes or unification hints. We also show how nonuniform coercions can be naturally implemented at the user level in an interactive theorem prover that allows unification hints.


Typed Operational Semantics for Dependent Record Types

Abstract: Typed operational semantics is a method developed by H. Goguen to prove meta-theoretic properties of type systems. This paper studies the metatheory of a type system with dependent record types, using the approach of typed operational semantics. In particular, the metatheoretical properties we have proved include strong normalisation, Church-Rosser and subject reduction.


Stateless HOL

Abstract: We present a version of the HOL Light system that supports undoing definitions in such a way that this does not compromise the soundness of the logic. In our system the code that keeps track of the constants that have been defined thus far has been moved out of the kernel. This means that the kernel now is purely functional. The changes to the system are small. All existing HOL Light developments can be run by the stateless system with only minor changes. The basic principle behind the system is not to name constants by strings, but by pairs consisting of a string and a definition. This means that the data structures for the terms are all merged into one big graph. OCaml - the implementation language of the system - can use pointer equality to establish equality of data structures fast. This allows the system to run at acceptable speeds. Our system runs at about 85% of the speed of the stateful version of HOL Light.


Confidentiality & Authentication Mechanism for Biometric Information Transmitted over Low Bandwidth & Unreliable channel

Abstract: The security of bio-metric information - finger print, retina mapping, DNA mapping and some other chemical and biological modified genes related information - transfer through low bandwidth and unreliable or covert channel is challenging task. Therefore, Security of biometric information is essential requirement in this fast developing communication world. Thus, in this paper, we propose efficient and effective mechanism for confidentiality and authentication for biometric information transmitted by using arithmetic encoding representation over low bandwidth and unreliable channel. It enhances the speed of encryption, decryption and authentication process. It uses arithmetic encoding scheme and public key cryptography e.g. modified version of RSA algorithm called RSA-2 algorithm.


A Robust Mechanism for Defending Distributed Denial OF Service Attacks on Web Servers

Abstract: Distributed Denial of Service (DDoS) attacks have emerged as a popular means of causing mass targeted service disruptions, often for extended periods of time. The relative ease and low costs of launching such attacks, supplemented by the current inadequate sate of any viable defense mechanism, have made them one of the top threats to the Internet community today. Since the increasing popularity of web-based applications has led to several critical services being provided over the Internet, it is imperative to monitor the network traffic so as to prevent malicious attackers from depleting the resources of the network and denying services to legitimate users. This paper first presents a brief discussion on some of the important types of DDoS attacks that currently exist and some existing mechanisms to combat these attacks. It then points out the major drawbacks of the currently existing defense mechanisms and proposes a new mechanism for protecting a web-server against a DDoS attack. In the proposed mechanism, incoming traffic to the server is continuously monitored and any abnormal rise in the inbound traffic is immediately detected. The detection algorithm is based on a statistical analysis of the inbound traffic on the server and a robust hypothesis testing framework. Simulations carried out on the proposed mechanism have produced results that demonstrate effectiveness of the proposed defense mechanism against DDoS attacks.


A Dynamic Multimedia User-Weight Classification Scheme for IEEE_802.11 WLANs

Abstract: In this paper we expose a dynamic traffic-classification scheme to support multimedia applications such as voice and broadband video transmissions over IEEE 802.11 Wireless Local Area Networks (WLANs). Obviously, over a Wi-Fi link and to better serve these applications - which normally have strict bounded transmission delay or minimum link rate requirement - a service differentiation technique can be applied to the media traffic transmitted by the same mobile node using the well-known 802.11e Enhanced Distributed Channel Access (EDCA) protocol. However, the given EDCA mode does not offer user differentiation, which can be viewed as a deficiency in multi-access wireless networks. Accordingly, we propose a new inter-node priority access scheme for IEEE 802.11e networks which is compatible with the EDCA scheme. The proposed scheme joins a dynamic user-weight to each mobile station depending on its outgoing data, and therefore deploys inter-node priority for the channel access to complement the existing EDCA inter-frame priority. This provides efficient quality of service control across multiple users within the same coverage area of an access point. We provide performance evaluations to compare the proposed access model with the basic EDCA 802.11 MAC protocol mode to elucidate the quality improvement achieved for multimedia communication over 802.11 WLANs.


Replication Attack Mitigations for Static and Mobile WSN

Abstract: Security is important for many sensor network applications. Wireless Sensor Networks (WSN) are often deployed in hostile environments as static or mobile, where an adversary can physically capture some of the nodes. once a node is captured, adversary collects all the credentials like keys and identity etc. the attacker can re-program it and replicate the node in order to eavesdrop the transmitted messages or compromise the functionality of the network. Identity theft leads to two types attack: clone and sybil. In particularly a harmful attack against sensor networks where one or more node(s) illegitimately claims an identity as replicas is known as the node replication attack. The replication attack can be exceedingly injurious to many important functions of the sensor network such as routing, resource allocation, misbehavior detection, etc. This paper analyzes the threat posed by the replication attack and several novel techniques to detect and defend against the replication attack, and analyzes their effectiveness in both static and mobile WSN.


A New Localized Network Based Routing Model in Computer and Communication networks

Abstract: In view of the fact that routing algorithms are network layer entities and the varying performance of any routing algorithm depends on the underlying networks. Localized routing algorithms avoid the problems associated with the maintenance of global network state by using statistics of flow blocking probabilities. We developed a new network parameter that can be used to predict which network topology gives better performance on the quality of localized QoS routing algorithms. Using this parameter we explore a simple model that can be rewired to introduce increasing the performance. We find that this model have small characteristic path length. Simulations of random and complex networks used to show that the performance is significantly affected by the level of connectivity.


An Integer Linear Programming Model for the Radiotherapy Treatment Scheduling Problem

Abstract: Radiotherapy represents an important phase of treatment for a large number of cancer patients. It is essential that resources used to deliver this treatment are employed effectively. This paper presents a new integer linear programming model for real-world radiotherapy treatment scheduling and analyses the effectiveness of using this model on a daily basis in a hospital. Experiments are conducted varying the days on which schedules can be created. Results obtained using real-world data from the Nottingham University Hospitals NHS Trust, UK, are presented and show how the proposed model can be used with different policies in order to achieve good quality schedules.


Finding Shortest Path for Developed Cognitive Map Using Medial Axis

Abstract: this paper presents an enhancement of the medial axis algorithm to be used for finding the optimal shortest path for developed cognitive map. The cognitive map has been developed, based on the architectural blueprint maps. The idea for using the medial-axis is to find main path central pixels; each center pixel represents the center distance between two side boarder pixels. The need for these pixels in the algorithm comes from the need of building a network of nodes for the path, where each node represents a turning in the real world (left, right, critical left, critical right...). The algorithm also ignores from finding the center pixels paths that are too small for intelligent robot navigation. The Idea of this algorithm is to find the possible shortest path between start and end points. The goal of this research is to extract a simple, robust representation of the shape of the cognitive map together with the optimal shortest path between start and end points. The intelligent robot will use this algorithm in order to decrease the time that is needed for sweeping the targeted building.


Extraction of handwritten areas from colored image of bank checks by an hybrid method

Abstract: One of the first step in the realization of an automatic system of check recognition is the extraction of the handwritten area. We propose in this paper an hybrid method to extract these areas. This method is based on digit recognition by Fourier descriptors and different steps of colored image processing . It requires the bank recognition of its code which is located in the check marking band as well as the handwritten color recognition by the method of difference of histograms. The areas extraction is then carried out by the use of some mathematical morphology tools.


Identification of arabic word from bilingual text using character features

Abstract: The identification of the language of the script is an important stage in the process of recognition of the writing. There are several works in this research area, which treat various languages. Most of the used methods are global or statistical. In this present paper, we study the possibility of using the features of scripts to identify the language. The identification of the language of the script by characteristics returns the identification in the case of multilingual documents less difficult. We present by this work, a study on the possibility of using the structural features to identify the Arabic language from an Arabic / Latin text.


Off-Line Handwritten Signature Identification Using Rotated Complex Wavelet Filters

Abstract: In this paper, a new method for handwritten signature identification based on rotated complex wavelet filters is proposed. We have proposed to use the rotated complex wavelet filters (RCWF) and dual tree complex wavelet transform(DTCWT) together to derive signature feature extraction, which captures information in twelve different directions. In identification phase, Canberra distance measure is used. The proposed method is compared with discrete wavelet transform (DWT). From experimental results it is found that signature identification rate of proposed method is superior over DWT


Self-Stabilization, Byzantine Containment, and Maximizable Metrics: Necessary Conditions

Abstract: Self-stabilization is a versatile approach to fault-tolerance since it permits a distributed system to recover from any transient fault that arbitrarily corrupts the contents of all memories in the system. Byzantine tolerance is an attractive feature of distributed systems that permits to cope with arbitrary malicious behaviors. We consider the well known problem of constructing a maximum metric tree in this context. Combining these two properties leads to some impossibility results. In this paper, we provide two necessary conditions to construct maximum metric tree in presence of transients and (permanent) Byzantine faults.


Distributed Learning Policies for Power Allocation in Multiple Access Channels

Abstract: We analyze the problem of distributed power allocation for orthogonal multiple access channels by considering a continuous non-cooperative game whose strategy space represents the users' distribution of transmission power over the network's channels. When the channels are static, we find that this game admits an exact potential function and this allows us to show that it has a unique equilibrium almost surely. Furthermore, using the game's potential property, we derive a modified version of the replicator dynamics of evolutionary game theory which applies to this continuous game, and we show that if the network's users employ a distributed learning scheme based on these dynamics, then they converge to equilibrium exponentially quickly. On the other hand, a major challenge occurs if the channels do not remain static but fluctuate stochastically over time, following a stationary ergodic process. In that case, the associated ergodic game still admits a unique equilibrium, but the learning analysis becomes much more complicated because the replicator dynamics are no longer deterministic. Nonetheless, by employing results from the theory of stochastic approximation, we show that users still converge to the game's unique equilibrium. Our analysis hinges on a game-theoretical result which is of independent interest: in finite player games which admit a (possibly nonlinear) convex potential function, the replicator dynamics (suitably modified to account for nonlinear payoffs) converge to an eps-neighborhood of an equilibrium at time of order O(log(1/eps)).


Detect Related Bugs from Source Code Using Bug Information

Abstract: Open source projects often maintain open bug repositories during development and maintenance, and the reporters often point out straightly or implicitly the reasons why bugs occur when they submit them. The comments about a bug are very valuable for developers to locate and fix the bug. Meanwhile, it is very common in large software for programmers to override or overload some methods according to the same logic. If one method causes a bug, it is obvious that other overridden or overloaded methods maybe cause related or similar bugs. In this paper, we propose and implement a tool Rebug- Detector, which detects related bugs using bug information and code features. Firstly, it extracts bug features from bug information in bug repositories; secondly, it locates bug methods from source code, and then extracts code features of bug methods; thirdly, it calculates similarities between each overridden or overloaded method and bug methods; lastly, it determines which method maybe causes potential related or similar bugs. We evaluate Rebug-Detector on an open source project: Apache Lucene-Java. Our tool totally detects 61 related bugs, including 21 real bugs and 10 suspected bugs, and it costs us about 15.5 minutes. The results show that bug features and code features extracted by our tool are useful to find real bugs in existing projects.


Incremental dimension reduction of tensors with random index

Abstract: We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable. Component encoding and decoding are performed on-line without computationally expensive re-analysis of the data set. The range of tensor indices can be extended dynamically without modifying the component representation. This idea originates from a mathematical model of semantic memory and a method known as random indexing in natural language processing. We generalize the random-indexing algorithm to tensors and present signal-to-noise-ratio simulations for representations of vectors and matrices. We present also a mathematical analysis of the approximate orthogonality of high-dimensional ternary vectors, which is a property that underpins this and other similar random-coding approaches to dimension reduction. To further demonstrate the properties of random indexing we present results of a synonym identification task. The method presented here has some similarities with random projection and Tucker decomposition, but it performs well at high dimensionality only (n>10^3). Random indexing is useful for a range of complex practical problems, e.g., in natural language processing, data mining, pattern recognition, event detection, graph searching and search engines. Prototype software is provided. It supports encoding and decoding of tensors of order >= 1 in a unified framework, i.e., vectors, matrices and higher order tensors.


Globalisation of science in kilometres

Abstract: The ongoing globalisation of science has undisputedly a major impact on how and where scientific research is being conducted nowadays. Yet, the big picture remains blurred. It is largely unknown where this process is heading, and at which rate. Which countries are leading or lagging? Many of its key features are difficult if not impossible to capture in measurements and comparative statistics. Our empirical study measures the extent and growth of scientific globalisation in terms of physical distances between co-authoring researchers. Our analysis, drawing on 21 million research publications across all countries and fields of science, reveals that contemporary science has globalised at a fairly steady rate during recent decades. The average collaboration distance per publication has increased from 334 kilometres in 1980 to 1553 in 2009. Despite significant differences in globalisation rates across countries and fields of science, we observe a pervasive process in motion, moving towards a truly interconnected global science system.


Easy Impossibility Proofs for k-Set Agreement in Message Passing Systems

Abstract: Despite of being quite similar agreement problems, consensus and general k-set agreement require surprisingly different techniques for proving the impossibility in asynchronous systems with crash failures: Rather than relatively simple bivalence arguments as in the impossibility proof for consensus (= 1-set agreement) in the presence of a single crash failure, known proofs for the impossibility of k-set agreement in systems with at least k>1 crash failures use algebraic topology or a variant of Sperner's Lemma. In this paper, we present a generic theorem for proving the impossibility of k-set agreement in various message passing settings, which is based on a simple reduction to the consensus impossibility in a certain subsystem. We demonstrate the broad applicability of our result by exploring the possibility/impossibility border of k-set agreement in several message-passing system models: (i) asynchronous systems with crash failures, (ii) partially synchronous processes with (initial) crash failures, and (iii) asynchronous systems augmented with failure detectors. In (i) and (ii), the impossibility part is just an instantiation of our main theorem, whereas the possibility of achieving k-set agreement in (ii) follows by generalizing the consensus algorithm for initial crashes by Fisher, Lynch and Patterson. In (iii), applying our technique yields the exact border for the parameter k where k-set agreement is solvable with the failure detector class (Sigma_k,Omega_k), for (1<= k<= n-1), of Bonnet and Raynal. Considering that Sigma_k was shown to be necessary for solving k-set agreement, this result yields new insights on the quest for the weakest failure detector.


Integration of Communication Analysis and the OO-Method: Rules for the manual derivation of the Conceptual Model

Abstract: Enterprise information systems can be developed following a model-driven paradigm. This way, models that represent the organisational work practice are used to produce models that represent the information system. Current software development methods are starting to provide guidelines for the construction of conceptual models, taking as input requirements models. This paper proposes the integration of two methods: Communication Analysis (a communication-oriented requirements engineering method [Espa\~na, Gonz\'alez et al. 2009]) and the OO-Method (a model-driven object-oriented software development method [Pastor and Molina 2007]). For this purpose, a systematic technique for deriving OO-Method Conceptual Models from business process and requirements models is proposed. The business process specifications (which include message structures) are processed in order to obtain static and dynamic views of the computerised information system. Then, using the OLIVANOVA framework, software source code can be generated automatically [CARE Technologies].


Cost Based Satisficing Search Considered Harmful

Abstract: Recently, several researchers have found that cost-based satisficing search with A* often runs into problems. Although some "work arounds" have been proposed to ameliorate the problem, there has not been any concerted effort to pinpoint its origin. In this paper, we argue that the origins can be traced back to the wide variance in action costs that is observed in most planning domains. We show that such cost variance misleads A* search, and that this is no trifling detail or accidental phenomenon, but a systemic weakness of the very concept of "cost-based evaluation functions + systematic search + combinatorial graphs". We show that satisficing search with sized-based evaluation functions is largely immune to this problem.


Optimal channel allocation with dynamic power control in cellular networks

Abstract: Techniques for channel allocation in cellular networks have been an area of intense research interest for many years. An efficient channel allocation scheme can significantly reduce call-blocking and calldropping probabilities. Another important issue is to effectively manage the power requirements for communication. An efficient power control strategy leads to reduced power consumption and improved signal quality. In this paper, we present a novel integer linear program (ILP) formulation that jointly optimizes channel allocation and power control for incoming calls, based on the carrier-to-interference ratio (CIR). In our approach we use a hybrid channel assignment scheme, where an incoming call is admitted only if a suitable channel is found such that the CIR of all ongoing calls on that channel, as well as that of the new call, will be above a specified value. Our formulation also guarantees that the overall power requirement for the selected channel will be minimized as much as possible and that no ongoing calls will be dropped as a result of admitting the new call. We have run simulations on a benchmark 49 cell environment with 70 channels to investigate the effect of different parameters such as the desired CIR. The results indicate that our approach leads to significant improvements over existing techniques.


Subclasses of Normal Helly Circular-Arc Graphs

Abstract: A Helly circular-arc model M = (C,A) is a circle C together with a Helly family \A of arcs of C. If no arc is contained in any other, then M is a proper Helly circular-arc model, if every arc has the same length, then M is a unit Helly circular-arc model, and if there are no two arcs covering the circle, then M is a normal Helly circular-arc model. A Helly (resp. proper Helly, unit Helly, normal Helly) circular-arc graph is the intersection graph of the arcs of a Helly (resp. proper Helly, unit Helly, normal Helly) circular-arc model. In this article we study these subclasses of Helly circular-arc graphs. We show natural generalizations of several properties of (proper) interval graphs that hold for some of these Helly circular-arc subclasses. Next, we describe characterizations for the subclasses of Helly circular-arc graphs, including forbidden induced subgraphs characterizations. These characterizations lead to efficient algorithms for recognizing graphs within these classes. Finally, we show how do these classes of graphs relate with straight and round digraphs.


Refining Recency Search Results with User Click Feedback

Abstract: Traditional machine-learned ranking systems for web search are often trained to capture stationary relevance of documents to queries, which has limited ability to track non-stationary user intention in a timely manner. In recency search, for instance, the relevance of documents to a query on breaking news often changes significantly over time, requiring effective adaptation to user intention. In this paper, we focus on recency search and study a number of algorithms to improve ranking results by leveraging user click feedback. Our contributions are three-fold. First, we use real search sessions collected in a random exploration bucket for \emph{reliable} offline evaluation of these algorithms, which provides an unbiased comparison across algorithms without online bucket tests. Second, we propose a re-ranking approach to improve search results for recency queries using user clicks. Third, our empirical comparison of a dozen algorithms on real-life search data suggests importance of a few algorithmic choices in these applications, including generalization across different query-document pairs, specialization to popular queries, and real-time adaptation of user clicks.


The AllDifferent Constraint with Precedences

Abstract: We propose AllDiffPrecedence, a new global constraint that combines together an AllDifferent constraint with precedence constraints that strictly order given pairs of variables. We identify a number of applications for this global constraint including instruction scheduling and symmetry breaking. We give an efficient propagation algorithm that enforces bounds consistency on this global constraint. We show how to implement this propagator using a decomposition that extends the bounds consistency enforcing decomposition proposed for the AllDifferent constraint. Finally, we prove that enforcing domain consistency on this global constraint is NP-hard in general.


On the Scalability of Multidimensional Databases

Abstract: It is commonly accepted in the practice of on-line analytical processing of databases that the multidimensional database organization is less scalable than the relational one. It is easy to see that the size of the multidimensional organization may increase very quickly. For example, if we introduce one additional dimension, then the total number of possible cells will be at least doubled. However, this reasoning does not takethe fact into account that the multidimensional organization can be compressed. There are compression techniques, which can remove all or at least a part of the empty cells from the multidimensional organization, while maintaining a good retrieval performance. Relational databases often use B-tree indices to speed up the access to given rows of tables. It can be proven, under some reasonable assumptions, that the total size of the table and the B-tree index is bigger than a compressed multidimensional representation. This implies that the compressed array results in a smaller database and faster access at the same time. This paper compares several compression techniques and shows when we should and should not apply compressed arrays instead of relational tables.


SafeZone: A Hierarchical Inter-Domain Authenticated Source Address Validation Solution

Abstract: Next generation Internet is highly concerned about the issue of reliability. Principally, the foundation of reliability is authentication of the source IP address. With the signature-and-verification based defense mechanisms available today, unfortunately, there is a lack of hierarchical architecture, which makes the structure of the trust alliance excessively flat and single. Moreover, with the increasing scale of the trust alliance, costs of validation grow so quickly that they do not adapt to incremental deployment. Via comparison with traditional solutions, this article proposes a hierarchical, inter-domain authenticated source address validation solution named SafeZone. SafeZone employs two intelligent designs, lightweight tag replacement and a hierarchical partitioning scheme, each of which helps to ensure that SafeZone can construct trustworthy and hierarchical trust alliances without the negative influences and complex operations on de facto networks. Extensive experiments also indicate that SafeZone can effectively obtain the design goals of a hierarchical architecture, along with lightweight, loose coupling and "multi-fence support" and as well as an incremental deployment scheme.


Validation Measures in CMMI

Abstract: Validation is one of the software engineering disciplines that help build quality into software. The major objective of software validation process is to determine that the software performs its intended functions correctly and provide information about its quality and reliability. This paper identifies general measures for the specific goals and its specific practices of Validation Process Area (PA) in Capability Maturity Model Integration (CMMI). CMMI is developed by Software Engineering Institute (SEI). CMMI is a framework for improvement and assessment of a software development process. CMMI needs a measurement program that is practical. The method we used to define the measures is to apply the Goal Question Metrics (GQM) paradigm to the specific goals and its specific practices of Validation Process Area in CMMI.


Learning Equilibrium Play for Stochastic Parallel Gaussian Interference Channels

Abstract: Distributed power control for parallel Gaussian interference channels recently draws great interests. However, all existing works only studied this problem under deterministic communication channels and required certain perfect information to carry out their proposed algorithms. In this paper, we study this problem for stochastic parallel Gaussian interference channels. In particular, we take into account the randomness of the communication environment and the estimation errors of the desired information, and thus formulate a stochastic noncooperative power control game. We then propose a stochastic distributed learning algorithm SDLA-I to help communication pairs learn the Nash equilibrium. A careful convergence analysis on SDLA-I is provided based on stochastic approximation theory and projected dynamic systems approach. We further propose another learning algorithm SDLA-II by including a simple iterate averaging idea into SDLA-I to improve algorithmic convergence performance. Numerical results are also presented to demonstrate the performance of our algorithms and theoretical results.


Image Encryption Based on Diffusion and Multiple Chaotic Maps

Abstract: In the recent world, security is a prime important issue, and encryption is one of the best alternative way to ensure security. More over, there are many image encryption schemes have been proposed, each one of them has its own strength and weakness. This paper presents a new algorithm for the image encryption/decryption scheme. This paper is devoted to provide a secured image encryption technique using multiple chaotic based circular mapping. In this paper, first, a pair of sub keys is given by using chaotic logistic maps. Second, the image is encrypted using logistic map sub key and in its transformation leads to diffusion process. Third, sub keys are generated by four different chaotic maps. Based on the initial conditions, each map may produce various random numbers from various orbits of the maps. Among those random numbers, a particular number and from a particular orbit are selected as a key for the encryption algorithm. Based on the key, a binary sequence is generated to control the encryption algorithm. The input image of 2-D is transformed into a 1- D array by using two different scanning pattern (raster and Zigzag) and then divided into various sub blocks. Then the position permutation and value permutation is applied to each binary matrix based on multiple chaos maps. Finally the receiver uses the same sub keys to decrypt the encrypted images. The salient features of the proposed image encryption method are loss-less, good peak signal-to-noise ratio (PSNR), Symmetric key encryption, less cross correlation, very large number of secret keys, and key-dependent pixel value replacement.


Stage Staffing Scheme for Copyright Protection in Multimedia

Abstract: Copyright protection has become a need in today's world. To achieve a secure copyright protection we embedded some information in images and videos and that image or video is called copyright protected. The embedded information can't be detected by human eye but some attacks and operations can tamper that information to breach protection. So in order to find a secure technique of copyright protection, we have analyzed image processing techniques i.e. Spatial Domain (Least Significant Bit (LSB)), Transform Domain (Discrete Cosine Transform (DCT)), Discrete Wavelet Transform (DWT) and there are numerous algorithm for watermarking using them. After having a good understanding of the same we have proposed a novel algorithm named as Stage Staffing Algorithm that generates results with high effectiveness, additionally we can use self extracted-watermark technique to increase the security and automate the process of watermark image. The proposed algorithm provides protection in three stages. We have implemented the algorithm and results of the simulations are shown. The various factors affecting spatial domain watermarking are also discussed.


Framework for Clique-based Fusion of Graph Streams in Multi-function System Testing

Abstract: The paper describes a framework for multi-function system testing. Multi-function system testing is considered as fusion (or revelation) of clique-like structures. The following sets are considered: (i) subsystems (system parts or units / components / modules), (ii) system functions and a subset of system components for each system function, and (iii) function clusters (some groups of system functions which are used jointly). Test procedures (as units testing) are used for each subsystem. The procedures lead to an ordinal result (states, colors) for each component, e.g., [1,2,3,4] (where 1 corresponds to 'out of service', 2 corresponds to 'major faults', 3 corresponds to 'minor faults', 4 corresponds to 'trouble free service'). Thus, for each system function a graph over corresponding system components is examined while taking into account ordinal estimates/colors of the components. Further, an integrated graph (i.e., colored graph) for each function cluster is considered (this graph integrates the graphs for corresponding system functions). For the integrated graph (for each function cluster) structure revelation problems are under examination (revelation of some subgraphs which can lead to system faults): (1) revelation of clique and quasi-clique (by vertices at level 1, 2, etc.; by edges/interconnection existence) and (2) dynamical problems (when vertex colors are functions of time) are studied as well: existence of a time interval when clique or quasi-clique can exist. Numerical examples illustrate the approach and problems.


A New Proposed Dynamic Quantum with Re-Adjusted Round Robin Scheduling Algorithm and Its Performance Analysis

Abstract: Scheduling is the central concept used frequently in Operating System. It helps in choosing the processes for execution. Round Robin (RR) is one of the most widely used CPU scheduling algorithm. But, its performance degrades with respect to context switching, which is an overhead and it occurs during each scheduling. Overall performance of the system depends on choice of an optimal time quantum, so that context switching can be reduced. In this paper, we have proposed a new variant of RR scheduling algorithm, known as Dynamic Quantum with Readjusted Round Robin (DQRRR) algorithm. We have experimentally shown that performance of DQRRR is better than RR by reducing number of context switching, average waiting time and average turn around time.


A New Dynamic Round Robin and SRTN Algorithm with Variable Original Time Slice and Intelligent Time Slice for Soft Real Time Systems

Abstract: The main objective of the paper is to improve the Round Robin (RR) algorithm using dynamic ITS by coalescing it with Shortest Remaining Time Next (SRTN) algorithm thus reducing the average waiting time, average turnaround time and the number of context switches. The original time slice has been calculated for each process based on its burst time.This is mostly suited for soft real time systems where meeting of deadlines is desirable to increase its performance. The advantage is that processes that are closer to their remaining completion time will get more chances to execute and leave the ready queue. This will reduce the number of processes in the ready queue by knocking out short jobs relatively faster in a hope to reduce the average waiting time, turn around time and number of context switches. This paper improves the algorithm [8] and the experimental analysis shows that the proposed algorithm performs better than algorithm [6] and [8] when the processes are having an increasing order, decreasing order and random order of burst time.


Composition of Management System for Smart Homes

Abstract: The paper addresses modular hierarchical design (composition) of a management system for smart homes. The management system consists of security subsystem (access control, alarm control), comfort subsystem (temperature, etc.), intelligence subsystem (multimedia, houseware). The design solving process is based on Hierarchical Morphological Multicriteria Design (HMMD) approach: (1) design of a tree-like system model, (2) generation of design alternatives for leaf nodes of the system model, (3) Bottom-Up process: (i) multicriteria selection of design alternatives for system parts/components and (ii) composing the selected alternatives into a resultant combination (while taking into account ordinal quality of the alternatives above and their compatibility). A realistic numerical example illustrates the design process of a management system for smart homes.


Course on System Design (structural approach)

Abstract: The article describes a course on system design (structural approach) which involves the following: issues of systems engineering; structural models; basic technological problems (structural system modeling, modular design, evaluation/comparison, revelation of bottlenecks, improvement/upgrade, multistage design, modeling of system evolution); solving methods (optimization, combinatorial optimization, multicriteria decision making); design frameworks; and applications. The course contains lectures and a set of special laboratory works. The laboratory works consist in designing and implementing a set of programs to solve multicriteria problems (ranking/selection, multiple choice problem, clustering, assignment). The programs above are used to solve some standard problems (e.g., hierarchical design of a student plan, design of a marketing strategy). Concurrently, each student can examine a unique applied problem from his/her applied domain(s) (e.g., telemetric system, GSM network, integrated security system, testing of microprocessor systems, wireless sensor, corporative communication network, network topology). Mainly, the course is targeted to developing the student skills in modular analysis and design of various multidisciplinary composite systems (e.g., software, electronic devices, information, computers, communications). The course was implemented in Moscow Institute of Physics and Technology (State University).


Difference Sequence Compression of Multidimensional Databases

Abstract: The multidimensional databases often use compression techniques in order to decrease the size of the database. This paper introduces a new method called difference sequence compression. Under some conditions, this new technique is able to create a smaller size multidimensional database than others like single count header compression, logical position compression or base-offset compression. Keywords: compression, multidimensional database, On-line Analytical Processing, OLAP.


Multidimensional or Relational? / How to Organize an On-line Analytical Processing Database

Abstract: In the past few years, the number of OLAP applications increased quickly. These applications use two significantly different DB structures: multidimensional (MD) and table-based. One can show that the traditional model of relational databases cannot make difference between these two structures. Another model is necessary to make the differences visible. One of these is the speed of the system. It can be proven that the multidimensional DB organization results in shorter response times. And it is crucial, since a manager may become impatient, if he or she has to wait say more than 20 seconds for the next screen. On the other hand, we have to pay for the speed with a bigger DB size. Why does the size of MD databases grow so quickly? The reason is the sparsity of data: The MD matrix contains many empty cells. Efficient handling of sparse matrices is indispensable in an OLAP application. One way to handle sparsity is to take the structure closer to the table-based one. Thus the DB size decreases, while the application gets slower. Therefore, other methods are needed. This paper deals with the comparison of the two DB structures and the limits of their usage. The new results of the paper: (1) It gives a constructive proof that all relations can be represented in MD arrays. (2) It also shows when the MD array representation is quicker than the table-based one. (3) The MD representation results in smaller DB size under some conditions. One such sufficient condition is proved in the paper. (4) A variation of the single count header compression scheme is described with an algorithm, which creates the compressed array from the ordered table without materializing the uncompressed array. (5) The speed of the two different database organizations is tested with experiments, as well. The tests are done on benchmark as well as real life data. The experiments support the theoretical results.


Improved Examples of Non-Termination for Ruppert's Algorithm

Abstract: Improving the best known examples, two planar straight-line graphs which cause the non-termination of Ruppert's algorithm for a minimum angle threshold as low as 29.06 degrees are given.


Informed Heuristics for Guiding Stem-and-Cycle Ejection Chains

Abstract: The state of the art in local search for the Traveling Salesman Problem is dominated by ejection chain methods utilising the Stem-and-Cycle reference structure. Though effective such algorithms employ very little information in their successor selection strategy, typically seeking only to minimise the cost of a move. We propose an alternative approach inspired from the AI literature and show how an admissible heuristic can be used to guide successor selection. We undertake an empirical analysis and demonstrate that this technique often produces better results than less informed strategies albeit at the cost of running in higher polynomial time.


Computing Shortest Paths among Curved Obstacles in the Plane

Abstract: A fundamental problem in computational geometry is to compute an obstacle-avoiding Euclidean shortest path between two points in the plane. The case of this problem on polygonal obstacles is well studied. In this paper, we consider the problem version on curved obstacles, commonly modeled as splinegons. A splinegon can be viewed as replacing each edge of a polygon by a convex curved edge (polygons are special splinegons). Each curved edge is assumed to be of O(1) complexity. Given in the plane two points s and t and a set of $h$ pairwise disjoint splinegons with a total of $n$ vertices, we compute a shortest s-to-t path avoiding the splinegons, in $O(n+h\log^{1+\epsilon}h+k)$ time, where k is a parameter sensitive to the structures of the input splinegons and is upper-bounded by $O(h^2)$. In particular, when all splinegons are convex, $k$ is proportional to the number of common tangents in the free space (called "free common tangents") among the splinegons. We develop techniques for solving the problem on the general (non-convex) splinegon domain, which also improve several previous results. In particular, our techniques produce an optimal output-sensitive algorithm for a basic visibility problem of computing all free common tangents among $h$ pairwise disjoint convex splinegons with a total of $n$ vertices. Our algorithm runs in $O(n+h\log h+k)$ time and $O(n)$ space, where $k$ is the number of all free common tangents. Even for the special case where all splinegons are convex polygons, the previously best algorithm for this visibility problem takes $O(n+h^2\log n)$ time.


A Goal-Directed Implementation of Query Answering for Hybrid MKNF Knowledge Bases

Abstract: Ontologies and rules are usually loosely coupled in knowledge representation formalisms. In fact, ontologies use open-world reasoning while the leading semantics for rules use non-monotonic, closed-world reasoning. One exception is the tightly-coupled framework of Minimal Knowledge and Negation as Failure (MKNF), which allows statements about individuals to be jointly derived via entailment from an ontology and inferences from rules. Nonetheless, the practical usefulness of MKNF has not always been clear, although recent work has formalized a general resolution-based method for querying MKNF when rules are taken to have the well-founded semantics, and the ontology is modeled by a general oracle. That work leaves open what algorithms should be used to relate the entailments of the ontology and the inferences of rules. In this paper we provide such algorithms, and describe the implementation of a query-driven system, CDF-Rules, for hybrid knowledge bases combining both (non-monotonic) rules under the well-founded semantics and a (monotonic) ontology, represented by a CDF Type-1 (ALQ) theory. To appear in Theory and Practice of Logic Programming (TPLP)


Non-Price Equilibria in Markets of Discrete Goods

Abstract: We study markets of indivisible items in which price-based (Walrasian) equilibria often do not exist due to the discrete non-convex setting. Instead we consider Nash equilibria of the market viewed as a game, where players bid for items, and where the highest bidder on an item wins it and pays his bid. We first observe that pure Nash-equilibria of this game excatly correspond to price-based equilibiria (and thus need not exist), but that mixed-Nash equilibria always do exist, and we analyze their structure in several simple cases where no price-based equilibrium exists. We also undertake an analysis of the welfare properties of these equilibria showing that while pure equilibria are always perfectly efficient ("first welfare theorem"), mixed equilibria need not be, and we provide upper and lower bounds on their amount of inefficiency.


BoolVar/PB v1.0, a java library for translating pseudo-Boolean constraints into CNF formulae

Abstract: BoolVar/PB is an open source java library dedicated to the translation of pseudo-Boolean constraints into CNF formulae. Input constraints can be categorized with tags. Several encoding schemes are implemented in a way that each input constraint can be translated using one or several encoders, according to the related tags. The library can be easily extended by adding new encoders and / or new output formats.


Delay Constrained Throughput Analysis of a Correlated MIMO Wireless Channel

Abstract: The maximum traffic arrival rate at the network for a given delay guarantee (delay constrained throughput) has been well studied for wired channels. However, few results are available for wireless channels, especially when multiple antennas are employed at the transmitter and receiver. In this work, we analyze the network delay constrained throughput of a multiple input multiple output (MIMO) wireless channel with time-varying spatial correlation. The MIMO channel is modeled via its virtual representation, where the individual spatial paths between the antenna pairs are Gilbert-Elliot channels. The whole system is then described by a K-State Markov chain, where K depends upon the degree of freedom (DOF) of the channel. We prove that the DOF based modeling is indeed accurate. Furthermore, we study the impact of the delay requirements at the network layer, violation probability and the number of antennas on the throughput under different fading speeds and signal strength.


Software is a directed multigraph (and so is software process)

Abstract: For a software system, its architecture is typically defined as the fundamental organization of the system incorporated by its components, their relationships to one another and their environment, and the principles governing their design. If contributed to by the artifacts coresponding to engineering processes that govern the system's evolution, the definition gets natually extended into the architecture of software and software process. Obviously, as long as there were no software systems, managing their architecture was no problem at all; when there were only small systems, managing their architecture became a mild problem; and now we have gigantic software systems, and managing their architecture has become an equally gigantic problem (to paraphrase Edsger Dijkstra). In this paper we propose a simple, yet we believe effective, model for organizing architecture of software systems. First of all we postulate that only a hollistic approach that supports continuous integration and verification for all software and software process architectural artifacts is the one worth taking. Next we indicate a graph-based model that not only allows collecting and maintaining the architectural knowledge in respect to both software and software process, but allows to conveniently create various quantitive metric to asses their respective quality or maturity. Such model is actually independent of the development methodologies that are currently in-use, that is it could well be applied for projects managed in an adaptive, as well as in a formal approach. Eventually we argue that the model could actually be implemented by already existing tools, in particular graph databases are a convenient implementation of architectural repository.


Efficient Resource Oblivious Algorithms for Multicores

Abstract: We consider the design of efficient algorithms for a multicore computing environment with a global shared memory and p cores, each having a cache of size M, and with data organized in blocks of size B. We characterize the class of `Hierarchical Balanced Parallel (HBP)' multithreaded computations for multicores. HBP computations are similar to the hierarchical divide & conquer algorithms considered in recent work, but have some additional features that guarantee good performance even when accounting for the cache misses due to false sharing. Most of our HBP algorithms are derived from known cache-oblivious algorithms with high parallelism, however we incorporate new techniques that reduce the effect of false-sharing. Our approach to addressing false sharing costs (or more generally, block misses) is to ensure that any task that can be stolen shares O(1) blocks with other tasks. We use a gapping technique for computations that have larger than O(1) block sharing. We also incorporate the property of limited access writes analyzed in a companion paper, and we bound the cost of accessing shared blocks on the execution stacks of tasks. We present the Priority Work Stealing (PWS) scheduler, and we establish that, given a sufficiently `tall' cache, PWS deterministically schedules several highly parallel HBP algorithms, including those for scans, matrix computations and FFT, with cache misses bounded by the sequential complexity, when accounting for both traditional cache misses and for false sharing. We also present a list ranking algorithm with almost optimal bounds. PWS schedules without using cache or block size information, and uses knowledge of processors only to the extent of determining the available locations from which tasks may be stolen; thus it schedules resource-obliviously.


Modelling dynamic route choice of pedestrians to assess the criticality of building evacuation

Abstract: This paper presents an event-driven way finding algorithm for pedestrians in an evacuation scenario, which operates on a graph-based structure. The motivation of each pedestrian is to leave the facility. The events used to redirect pedestrians include the identification of a jam situation and/or identification of a better route than the current. This study considers two types of pedestrians: familiar and unfamiliar with the facility. Four strategies are modelled to cover those groups. The modelled strategies are the shortest path (local and global); They are combined with a quickest path approach, which is based on an observation principle. In the quickest path approach, pedestrians take their decisions based on the observed environment and are routed dynamically in the network using an appropriate cost benefit analysis function. The dynamic modelling of route choice with different strategies and types of pedestrians considers the manifold of in uences which appears in the real system and raises questions about the criticality of an evacuation process. To address this question criteria are elaborated. The criteria we focus on in this contribution are the evacuation time, the individual times spent in jam, the jam size evolution and the overall jam size itself. The in uences of the different strategies on those evaluation criteria are investigated. The sensibility of the system to disturbances (e.g. broken escape route) is also analysed. Keywords: pedestrian dynamics, routing, quickest path, evacuation, jam, critical state


Sampling-rate-aware noise generation

Abstract: In this paper we consider the generation of discrete white noise. Despite this seems to be a simple problem, common noise generator implementations do not deliver comparable results at different sampling rates. First we define what we mean with "comparable results". From this we conclude, that the variance of the random variables shall grow proportionally to the sampling rate. Eventually we consider how noise behaves under common signal transformations, such as frequency filters, quantisation and impulse generation and we explore how these signal transformations must be designed in order generate sampling-rate-aware results when applied to white noise.


An ER-based Framework for Declarative Web Programming

Abstract: We describe a framework to support the implementation of web-based systems intended to manipulate data stored in relational databases. Since the conceptual model of a relational database is often specified as an entity-relationship (ER) model, we propose to use the ER model to generate a complete implementation in the declarative programming language Curry. This implementation contains operations to create and manipulate entities of the data model, supports authentication, authorization, session handling, and the composition of individual operations to user processes. Furthermore, the implementation ensures the consistency of the database w.r.t. the data dependencies specified in the ER model, i.e., updates initiated by the user cannot lead to an inconsistent state of the database. In order to generate a high-level declarative implementation that can be easily adapted to individual customer requirements, the framework exploits previous works on declarative database programming and web user interface construction in Curry.


Analysis of Randomized Work Stealing with False Sharing

Abstract: This paper analyzes the cache miss cost of algorithms when scheduled using randomized work stealing (RWS) in a parallel environment, taking into account the effects of false sharing. First, prior analyses (due to Acar et al.) are extended to incorporate false sharing. However, to control the possible delays due to false sharing, some restrictions on the algorithms seem necessary. Accordingly, the class of Hierarchical Tree algorithms is introduced and their performance analyzed. In addition, the paper analyzes the performance of a subclass of the Hierarchical Tree Algorithms, called HBP algorithms, when scheduled using RWS; improved complexity bounds are obtained for this subclass. This class was introduced in a companion paper with efficient resource oblivious computation in mind. Finally, we note that in a scenario in which there is no false sharing the results in this paper match prior bounds for cache misses but with reduced assumptions, and in particular with no need for a bounding concave function for the cost of cache misses as in prior work by Frigo and Strumpen. This allows non-trivial cache miss bounds in this case to be obtained for a larger class of algorithms.


Caching in Multidimensional Databases

Abstract: One utilisation of multidimensional databases is the field of On-line Analytical Processing (OLAP). The applications in this area are designed to make the analysis of shared multidimensional information fast [9]. On one hand, speed can be achieved by specially devised data structures and algorithms. On the other hand, the analytical process is cyclic. In other words, the user of the OLAP application runs his or her queries one after the other. The output of the last query may be there (at least partly) in one of the previous results. Therefore caching also plays an important role in the operation of these systems. However, caching itself may not be enough to ensure acceptable performance. Size does matter: The more memory is available, the more we gain by loading and keeping information in there. Oftentimes, the cache size is fixed. This limits the performance of the multidimensional database, as well, unless we compress the data in order to move a greater proportion of them into the memory. Caching combined with proper compression methods promise further performance improvements. In this paper, we investigate how caching influences the speed of OLAP systems. Different physical representations (multidimensional and table) are evaluated. For the thorough comparison, models are proposed. We draw conclusions based on these models, and the conclusions are verified with empirical data.


Difference-Huffman Coding of Multidimensional Databases

Abstract: A new compression method called difference-Huffman coding (DHC) is introduced in this paper. It is verified empirically that DHC results in a smaller multidimensional physical representation than those for other previously published techniques (single count header compression, logical position compression, base-offset compression and difference sequence compression). The article examines how caching influences the expected retrieval time of the multidimensional and table representations of relations. A model is proposed for this, which is then verified with empirical data. Conclusions are drawn, based on the model and the experiment, about when one physical representation outperforms another in terms of retrieval time. Over the tested range of available memory, the performance for the multidimensional representation was always much quicker than for the table representation.


Gossip PCA

Abstract: Eigenvectors of data matrices play an important role in many computational problems, ranging from signal processing to machine learning and control. For instance, algorithms that compute positions of the nodes of a wireless network on the basis of pairwise distance measurements require a few leading eigenvectors of the distances matrix. While eigenvector calculation is a standard topic in numerical linear algebra, it becomes challenging under severe communication or computation constraints, or in absence of central scheduling. In this paper we investigate the possibility of computing the leading eigenvectors of a large data matrix through gossip algorithms. The proposed algorithm amounts to iteratively multiplying a vector by independent random sparsification of the original matrix and averaging the resulting normalized vectors. This can be viewed as a generalization of gossip algorithms for consensus, but the resulting dynamics is significantly more intricate. Our analysis is based on controlling the convergence to stationarity of the associated Kesten-Furstenberg Markov chain.


On Nash Dynamics of Matching Market Equilibria

Abstract: In this paper, we study the Nash dynamics of strategic interplays of n buyers in a matching market setup by a seller, the market maker. Taking the standard market equilibrium approach, upon receiving submitted bid vectors from the buyers, the market maker will decide on a price vector to clear the market in such a way that each buyer is allocated an item for which he desires the most (a.k.a., a market equilibrium solution). While such equilibrium outcomes are not unique, the market maker chooses one (maxeq) that optimizes its own objective --- revenue maximization. The buyers in turn change bids to their best interests in order to obtain higher utilities in the next round's market equilibrium solution. This is an (n+1)-person game where buyers place strategic bids to gain the most from the market maker's equilibrium mechanism. The incentives of buyers in deciding their bids and the market maker's choice of using the maxeq mechanism create a wave of Nash dynamics involved in the market. We characterize Nash equilibria in the dynamics in terms of the relationship between maxeq and mineq (i.e., minimum revenue equilibrium), and develop convergence results for Nash dynamics from the maxeq policy to a mineq solution, resulting an outcome equivalent to the truthful VCG mechanism. Our results imply revenue equivalence between maxeq and mineq, and address the question that why short-term revenue maximization is a poor long run strategy, in a deterministic and dynamic setting.


Parallel Online Learning

Abstract: In this work we study parallelization of online learning, a core primitive in machine learning. In a parallel environment all known approaches for parallel online learning lead to delayed updates, where the model is updated using out-of-date information. In the worst case, or when examples are temporally correlated, delay can have a very adverse effect on the learning algorithm. Here, we analyze and present preliminary empirical results on a set of learning architectures based on a feature sharding approach that present various tradeoffs between delay, degree of parallelism, representation power and empirical performance.


Universal Metadata Standard

Abstract: The creation of a next generation internet (semantic web) is impossible without attributes, allowing the semantic association of documents and their integration into information context. To achieve these goals, the Universal Metadata Standard (ums) may be an ultimative tool, which could serve as a basis for documentography, and is functionally required for interpretation of documents by the automatic operating systems.


Rendering of 3D Dynamic Virtual Environments

Abstract: In this paper we present a framework for the rendering of dynamic 3D virtual environments which can be integrated in the development of videogames. It includes methods to manage sounds and particle effects, paged static geometries, the support of a physics engine and various input systems. It has been designed with a modular structure to allow future expansions. We exploited some open-source state-of-the-art components such as OGRE, PhysX, ParticleUniverse, etc.; all of them have been properly integrated to obtain peculiar physical and environmental effects. The stand-alone version of the application is fully compatible with Direct3D and OpenGL APIs and adopts OpenAL APIs to manage audio cards. Concluding, we devised a showcase demo which reproduces a dynamic 3D environment, including some particular effects: the alternation of day and night infuencing the lighting of the scene, the rendering of terrain, water and vegetation, the reproduction of sounds and atmospheric agents.


Stratified B-trees and versioning dictionaries

Abstract: A classic versioned data structure in storage and computer science is the copy-on-write (CoW) B-tree -- it underlies many of today's file systems and databases, including WAFL, ZFS, Btrfs and more. Unfortunately, it doesn't inherit the B-tree's optimality properties; it has poor space utilization, cannot offer fast updates, and relies on random IO to scale. Yet, nothing better has been developed since. We describe the `stratified B-tree', which beats all known semi-external memory versioned B-trees, including the CoW B-tree. In particular, it is the first versioned dictionary to achieve optimal tradeoffs between space, query and update performance.


Undirected Connectivity of Sparse Yao Graphs

Abstract: Given a finite set S of points in the plane and a real value d > 0, the d-radius disk graph G^d contains all edges connecting pairs of points in S that are within distance d of each other. For a given graph G with vertex set S, the Yao subgraph Y_k[G] with integer parameter k > 0 contains, for each point p in S, a shortest edge pq from G (if any) in each of the k sectors defined by k equally-spaced rays with origin p. Motivated by communication issues in mobile networks with directional antennas, we study the connectivity properties of Y_k[G^d], for small values of k and d. In particular, we derive lower and upper bounds on the minimum radius d that renders Y_k[G^d] connected, relative to the unit radius assumed to render G^d connected. We show that d=sqrt(2) is necessary and sufficient for the connectivity of Y_4[G^d]. We also show that, for d <= ~1.056, the graph Y_3[G^d] can be disconnected, but for d >= 2/sqrt(3), Y_3[G^d] is always connected. Finally, we show that Y_2[G^d] can be disconnected, for any d >= 1.


The Stretch Factor of the Delaunay Triangulation Is Less Than 1.998

Abstract: Let $S$ be a finite set of points in the Euclidean plane. Let $D$ be a Delaunay triangulation of $S$. The {\em stretch factor} (also known as {\em dilation} or {\em spanning ratio}) of $D$ is the maximum ratio, among all points $p$ and $q$ in $S$, of the shortest path distance from $p$ to $q$ in $D$ over the Euclidean distance $||pq||$. Proving a tight bound on the stretch factor of the Delaunay triangulation has been a long standing open problem in computational geometry. In this paper we prove that the stretch factor of the Delaunay triangulation of a set of points in the plane is less than $\rho = 1.998$, improving the previous best upper bound of 2.42 by Keil and Gutwin (1989). Our bound 1.998 is better than the current upper bound of 2.33 for the special case when the point set is in convex position by Cui, Kanj and Xia (2009). This upper bound breaks the barrier 2, which is significant because previously no family of plane graphs was known to have a stretch factor guaranteed to be less than 2 on any set of points.


Multiply-Recursive Upper Bounds with Higman's Lemma

Abstract: We develop a new analysis for the length of controlled bad sequences in well-quasi-orderings based on Higman's Lemma. This leads to tight multiply-recursive upper bounds that readily apply to several verification algorithms for well-structured systems.


Distributed Inference and Query Processing for RFID Tracking and Monitoring

Abstract: In this paper, we present the design of a scalable, distributed stream processing system for RFID tracking and monitoring. Since RFID data lacks containment and location information that is key to query processing, we propose to combine location and containment inference with stream query processing in a single architecture, with inference as an enabling mechanism for high-level query processing. We further consider challenges in instantiating such a system in large distributed settings and design techniques for distributed inference and query processing. Our experimental results, using both real-world data and large synthetic traces, demonstrate the accuracy, efficiency, and scalability of our proposed techniques.


Security Features of an Asymmetric Cryptosystem based on the Diophantine Equation Hard Problem

Abstract: The Diophantine Equation Hard Problem (DEHP) is a potential cryptographic problem on the Diophantine equation $U=\sum \limits_{i=1}^n {V_i x_{i}}$. A proper implementation of DEHP would render an attacker to search for private parameters amongst the exponentially many solutions. However, an improper implementation would provide an attacker exponentially many choices to solve the DEHP. The AA\,$_{\beta}$-cryptosystem is an asymmetric cryptographic scheme that utilizes this concept together with the factorization problem of two large primes and is implemented only by using the multiplication operation for both encryption and decryption. With this simple mathematical structure, it would have low computational requirements and would enable communication devices with low computing power to deploy secure communication procedures efficiently.