Rozw\'oj bibliotek cyfrowych i repozytori\'ow elektronicznych na Dolnym Slasku w latach 2004-2008 / Development of Digital Libraries and Electronic Repositories in Lower Silesia in Years 2004-2008

Abstract: In following elaboration were presented digital libraries and electronic repositories operating in Lower Silesia region (of Poland) in years 2004-2008. General description of character and size of their collections was presented, as well as standards and methods of digital collections management and juridical aspects of this management. Potential of usage of digital collections in regional scientific researches was described. ----- W referacie przedstawiono biblioteki cyfrowe i repozytoria elektroniczne funkcjonujace na Dolnym Slasku w latach 2004-2008. Scharakteryzowano og\'olnie ich zawarto\'s\'c i wielko\'s\'c, zaprezentowano standardy i systemy zarzadzania kolekcjami cyfrowymi oraz om\'owiono uwarunkowania prawne towarzyszace zarzadzaniu zasobami cyfrowymi. Wskazano mo\.zliwo\'sci wykorzystania kolekcji cyfrowych w badaniach naukowych realizowanych w regionie.


Geodesic diameter of a polygonal domain in O(n^4 log n) time

Abstract: We show that the geodesic diameter of a polygonal domain with n vertices can be computed in O(n^4 log n) time by considering O(n^3) candidate diameter endpoints; the endpoints are a subset of vertices of the overlay of shortest path maps from vertices of the domain.


Stochastic Approximation Algorithm for Optimal Throughput Performance of Wireless LANs

Abstract: Throughput improvement of the Wireless LANs has been a constant area of research. Most of the work in this area, focuses on designing throughput optimal schemes for fully connected networks (no hidden nodes). But, we demonstrate that the proposed schemes, though perform optimally in fully connected network, achieve significantly lesser throughput even than that of standard IEEE 802.11 in a network with hidden nodes. This motivates the need for designing schemes that provide near optimal performance even when hidden nodes are present. The primary reason for the failure of existing protocols in the presence of hidden nodes is that these protocols are based on the model developed by Bianchi. However this model does not hold when hidden nodes exist. Moreover, analyzing networks with hidden nodes is still an open problem. Thus, designing throughput optimal schemes in networks with hidden nodes is particularly challenging. The novelty of our approach is that it is not based on any underlying mathematical model, rather it directly tunes the control variables so as to maximize the throughput. We demonstrate that this model independent approach achieves maximum throughput in networks with hidden terminals as well. Apart from this major contribution, we present stochastic approximation based algorithms for achieving weighted fairness in a connected networks. We also present a throughput optimal exponential backoff based random access algorithm. We demonstrate that the exponential backoff based scheme may outperform an optimal p-persistent scheme in networks with hidden terminals. This demonstrates the merit of exponential backoff based random access schemes which was deemed unnecessary by results shown by Bianchi.


Parameterized Two-Player Nash Equilibrium

Abstract: We study the computation of Nash equilibria in a two-player normal form game from the perspective of parameterized complexity. Recent results proved hardness for a number of variants, when parameterized by the support size. We complement those results, by identifying three cases in which the problem becomes fixed-parameter tractable. These cases occur in the previously studied settings of sparse games and unbalanced games as well as in the newly considered case of locally bounded treewidth games that generalizes both these two cases.


Efektifitas Teknologi Informasi Dalam Proses Belajar Mengajar Pada Universitas Budi Luhur

Abstract: In general, however, IT will empower students to have greater control over the learning process, with all the benefits associated with active learning and personal responsibility. Not only will students decide when to learn and how to learn, increasingly they will also decide what to learn and how that learning is to be certified. Traditionally, higher education institutions have combined several functions in their faculty. Faculty are architects as they design learning programs; navigators as they help advise students in their course of study; instructors when they lecture; mentors when they help students form a sense of connectedness to the world; and evaluators and certifiers as they decide to grant students grades or degrees.


Multidimensi Pada Data Warehouse Dengan Menggunakan Rumus Kombinasi

Abstract: Multidimensional in data warehouse is a compulsion and become the most important for information delivery, without multidimensional data warehouse is incomplete. Multidimensional give the able to analyze business measurement in many different ways. Multidimensional is also synonymous with online analytical processing (OLAP).


Sistem Informasi Akademik Online Sebagai Penunjang Sistem Perkuliahan

Abstract: The development of Internet technology give a chance for application in all kind of humans activity include education specially for higher education in university in order to increase education quality. In this paper we will discuss about the importance of the elements which must be fulfilled when we build the online academic application with web technology which will help teaching process in university. Also we will discuss to implement open source software as foundation in order to deploy the information system with low cost without losing the performance. In the future assembling internet technology on education and training will be need in order to enhancement and distribution education quality, specially in Indonesia where has many islands separate with sea and mountain. Students and faculty will enjoy access to multiple resources from one location, delivering search results with a range of content including encyclopedia articles, multimedia, related Web sites, magazines, and much more. Enables schools to implement an online academic program. It equips schools to host online courses, conduct live and blog-style communication between faculty and students, track grades, automate test scoring, store course materials, and much more.


Pemanfaatan Teknologi Sistem Informasi Geografis Untuk Menunjang Pembangunan Daerah

Abstract: The territory development will depend on that territory itself, where the word of autonomy for each province or territory will give contribution how Indonesian will responsible for development their territory. In order to develop territory, the information technology can be used as a boost or tools to give and deliver the best information and Geographic Information System is one of the information technology tools which can be used to push every each territory to speed the territory development. As a tool Geographic Information System has an ability to save, process, analysis and deliver information right in time and help the decision maker to make better decision.


Classification rule with simple select SQL statement

Abstract: A simple sql statement can be used to search learning or rule in relational database for data mining purposes particularly for classification rule. With just only one simple sql statement, characteristic and classification rule can be created simultaneously. Collaboration sql statement with any other application software will increase the ability for creating t-weight as measurement the typicality of each record in the characteristic rule and d-weight as measurement the discriminating behavior of the learned classification/discriminant rule, specifically for further generalization in characteristic rule. Handling concept hierarchy into tables based on concept tree will influence for the successful simple sql statement and by knowing the right standard knowledge to transform each of concept tree in concept hierarchy into one table as to transform concept hierarchy into table, the simple sql statement can be run properly.


Perbandingan Shell Unix

Abstract: Is it possible for an Information Technology [IT] product to be both mature and state-of-theart at the same time? In the case of the UNIX system, the answer is an unqualified "Yes." The UNIX system has continued to develop over the past twenty-five years. In millions of installations running on nearly every hardware platform made, the UNIX system has earned its reputation for stability and scalability. Over the years, UNIX system suppliers have steadily assimilated new technologies so that UNIX systems today provide more functionality as any other operating system.


Pembobolan website KPU (Komisi Pemilihan Umum) Apakah melanggar UU RI no.36 tahun 1999 tentang telekomunikasi ?

Abstract: Information Technology KPU (Indonesia Electoral Commision) is a project in supporting democratization process in Indonesia. It is a part of General Election program of KPU-Indonesian Government. The aim of IT KPU is to build the transparency of the ballot result to the public (citizen and international world) and as the embrio of e government in Indonesia. It also has the aim for influence the citizen with Information Technology and the use of computer.


Software Must Move! A Description of the Software Assembly Line

Abstract: This paper describes a set of tools for automating and controlling the development and maintenance of software systems. The mental model is a software assembly line. Program design and construction take place at individual programmer workstations. Integration of individual software components takes place at subsequent stations on the assembly line. Software is moved automatically along the assembly line toward final packaging. Software under construction or maintenance is divided into packages. Each package of software is composed of a recipe and ingredients. Some new terms are introduced to describe the ingredients. The recipe specifies how ingredients are transformed into products. The benefits of the Software Assembly Line for development, maintenance, and management of large-scale computer systems are explained.


Dyadic Prediction Using a Latent Feature Log-Linear Model

Abstract: In dyadic prediction, labels must be predicted for pairs (dyads) whose members possess unique identifiers and, sometimes, additional features called side-information. Special cases of this problem include collaborative filtering and link prediction. We present the first model for dyadic prediction that satisfies several important desiderata: (i) labels may be ordinal or nominal, (ii) side-information can be easily exploited if present, (iii) with or without side-information, latent features are inferred for dyad members, (iv) it is resistant to sample-selection bias, (v) it can learn well-calibrated probabilities, and (vi) it can scale to very large datasets. To our knowledge, no existing method satisfies all the above criteria. In particular, many methods assume that the labels are ordinal and ignore side-information when it is present. Experimental results show that the new method is competitive with state-of-the-art methods for the special cases of collaborative filtering and link prediction, and that it makes accurate predictions on nominal data.


Highly Parallel Sparse Matrix-Matrix Multiplication

Abstract: Generalized sparse matrix-matrix multiplication is a key primitive for many high performance graph algorithms as well as some linear solvers such as multigrid. We present the first parallel algorithms that achieve increasing speedups for an unbounded number of processors. Our algorithms are based on two-dimensional block distribution of sparse matrices where serial sections use a novel hypersparse kernel for scalability. We give a state-of-the-art MPI implementation of one of our algorithms. Our experiments show scaling up to thousands of processors on a variety of test scenarios.


MDPs with Unawareness

Abstract: Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision maker (DM) knows all states and actions. However, this may not be true in many situations of interest. We define a new framework, MDPs with unawareness (MDPUs) to deal with the possibilities that a DM may not be aware of all possible actions. We provide a complete characterization of when a DM can learn to play near-optimally in an MDPU, and give an algorithm that learns to play near-optimally when it is possible to do so, as efficiently as possible. In particular, we characterize when a near-optimal solution can be found in polynomial time.


The duality of computation under focus

Abstract: We review the close relationship between abstract machines for (call-by-name or call-by-value) lambda-calculi (extended with Felleisen's C) and sequent calculus, reintroducing on the way Curien-Herbelin's syntactic kit expressing the duality of computation. We use this kit to provide a term language for a presentation of LK (with conjunction, disjunction, and negation), and to transcribe cut elimination as (non confluent) rewriting. A key slogan here, which may appear here in print for the first time, is that commutative cut elimination rules are explicit substitution propagation rules. We then describe the focalised proof search discipline (in the classical setting), and narrow down the language and the rewriting rules to a confluent calculus (a variant of the second author's focalising system L). We then define a game of patterns and counterpatterns, leading us to a fully focalised finitary syntax for a synthetic presentation of classical logic, that provides a quotient on (focalised) proofs, abstracting out the order of decomposition of negative connectives.


Unification in the Description Logic EL

Abstract: The Description Logic EL has recently drawn considerable attention since, on the one hand, important inference problems such as the subsumption problem are polynomial. On the other hand, EL is used to define large biomedical ontologies. Unification in Description Logics has been proposed as a novel inference service that can, for example, be used to detect redundancies in ontologies. The main result of this paper is that unification in EL is decidable. More precisely, EL-unification is NP-complete, and thus has the same complexity as EL-matching. We also show that, w.r.t. the unification type, EL is less well-behaved: it is of type zero, which in particular implies that there are unification problems that have no finite complete set of unifiers.


Advanced Software Protection Now

Abstract: Software digital rights management is a pressing need for the software development industry which remains, as no practical solutions have been acclamaimed succesful by the industry. We introduce a novel software-protection method, fully implemented with today's technologies, that provides traitor tracing and license enforcement and requires no additional hardware nor inter-connectivity. Our work benefits from the use of secure triggers, a cryptographic primitive that is secure assuming the existence of an ind-cpa secure block cipher. Using our framework, developers may insert license checks and fingerprints, and obfuscate the code using secure triggers. As a result, this rises the cost that software analysis tools have detect and modify protection mechanisms. Thus rising the complexity of cracking this system.


Constructions from Dots and Lines

Abstract: A graph is a data structure composed of dots (i.e. vertices) and lines (i.e. edges). The dots and lines of a graph can be organized into intricate arrangements. The ability for a graph to denote objects and their relationships to one another allow for a surprisingly large number of things to be modeled as a graph. From the dependencies that link software packages to the wood beams that provide the framing to a house, most anything has a corresponding graph representation. However, just because it is possible to represent something as a graph does not necessarily mean that its graph representation will be useful. If a modeler can leverage the plethora of tools and algorithms that store and process graphs, then such a mapping is worthwhile. This article explores the world of graphs in computing and exposes situations in which graphical models are beneficial.


L2-optimal image interpolation and its applications to medical imaging

Abstract: Digital medical images are always displayed scaled to fit particular view. Interpolation is responsible for this scaling, and if not done properly, can significantly degrade diagnostic image quality. However, theoretically-optimal interpolation algorithms may also be the most time-consuming and impractical. We propose a new approach, adapted to the needs of digital medical imaging, to combine high interpolation speed and superior L2-optimal image quality.


Simulation of Computer Network Attacks

Abstract: In this work we present a prototype for simulating computer network attacks. Our objective is to simulate large networks (thousands of hosts, with applications and vulnerabilities) while remaining realistic from the attacker's point of view. The foundation for the simulator is a model of computer intrusions, based on the analysis of real world attacks. In particular we show how to interpret vulnerabilities and exploits as communication channels. This conceptual model gives a tool to describe the theater of operations, targets, actions and assets involved in multistep network attacks. We conclude with applications of the attack simulator.


An attack on MySQL's login protocol

Abstract: The MySQL challenge-and-response authentication protocol is proved insecure. We show how can an eavesdropper impersonate a valid user after witnessing only a few executions of this protocol. The algorithm of the underlying attack is presented. Finally we comment about implementations and statistical results.


Anonymous Gossiping

Abstract: In this paper we introduce a novel gossiping primitive to support privacy preserving data analytics (PPDA). In contrast to existing computational PPDA primitives such as secure multiparty computation and data randomization based approaches, the proposed primitive `anonymous gossiping' is a communication primitive for privacy preserving personalized information aggregation complementing such traditional computational analytics. We realize this novel primitive by composing existing gossiping mechanisms for peer sampling & information aggregation and onion routing technique for establishing anonymous communication. This is more an `ideas' paper, rather than providing concrete and quantified results.


Does Treewidth Help in Modal Satisfiability?

Abstract: Many tractable algorithms for solving the Constraint Satisfaction Problem (CSP) have been developed using the notion of the treewidth of some graph derived from the input CSP instance. In particular, the incidence graph of the CSP instance is one such graph. We introduce the notion of an incidence graph for modal logic formulae in a certain normal form. We investigate the parameterized complexity of modal satisfiability with the modal depth of the formula and the treewidth of the incidence graph as parameters. For various combinations of Euclidean, reflexive, symmetric and transitive models, we show either that modal satisfiability is FPT, or that it is W[1]-hard. In particular, modal satisfiability in general models is FPT, while it is W[1]-hard in transitive models. As might be expected, modal satisfiability in transitive and Euclidean models is FPT.


Mirrored Language Structure and Innate Logic of the Human Brain as a Computable Model of the Oracle Turing Machine

Abstract: We wish to present a mirrored language structure (MLS) and four logic rules determined by this structure for the model of a computable Oracle Turing machine. MLS has novel features that are of considerable biological and computational significance. It suggests an algorithm of relation learning and recognition (RLR) that enables the deterministic computers to simulate the mechanism of the Oracle Turing machine, or P = NP in a mathematical term.


The Application and Extension of Retrograde Software Analysis

Abstract: The retrograde software analysis is a method that emanates from executing a program backwards - instead of taking input data and following the execution path, we start from output data and by executing the program backwards, command by command, analyze data that could lead to the current output. The changed perspective forces a developer to think in a new way about the program. It can be applied as a thorough procedure or casual method. With this method, we have many advantages in testing, algorithm and system analysis.


Similarity Analysis and Modeling in Mobile Societies: The Missing Link

Abstract: A new generation of "behavior-aware" delay tolerant networks is emerging in what may define future mobile social networks. With the introduction of novel behavior-aware protocols, services and architectures, there is a pressing need to understand and realistically model mobile users behavioral characteristics, their similarity and clustering. Such models are essential for the analysis, performance evaluation, and simulation of future DTNs. This paper addresses issues related to mobile user similarity, its definition, analysis and modeling. To define similarity, we adopt a behavioral-profile based on users location preferences using their on-line association matrix and its SVD, then calculate the behavioral distance to capture user similarity. This measures the difference of the major spatio-temporal behavioral trends and can be used to cluster users into similarity groups or communities. We then analyze and contrast similarity distributions of mobile user populations in two settings: (i) based on real measurements from four major campuses with over ten thousand users for a month, and (ii) based on existing mobility models, including random direction and time-varying community models. Our results show a rich set of similar communities in real mobile societies with distinct behavioral clusters of users. This is true for all the traces studied, with the trend being consistent over time. Surprisingly, however, we find that the existing mobility models do not explicitly capture similarity and result in homogeneous users that are all similar to each other. Thus the richness and diversity of user behavioral patterns is not captured to any degree in the existing models. These findings strongly suggest that similarity should be explicitly captured in future mobility models, which motivates the need to re-visit mobility modeling in the future.


Agnostic Active Learning Without Constraints

Abstract: We present and analyze an agnostic active learning algorithm that works without keeping a version space. This is unlike all previous approaches where a restricted set of candidate hypotheses is maintained throughout learning, and only hypotheses from this set are ever returned. By avoiding this version space approach, our algorithm sheds the computational burden and brittleness associated with maintaining version spaces, yet still allows for substantial improvements over supervised learning for classification.


Gang FTP scheduling of periodic and parallel rigid real-time tasks

Abstract: In this paper we consider the scheduling of periodic and parallel rigid tasks. We provide (and prove correct) an exact schedulability test for Fixed Task Priority (FTP) Gang scheduler sub-classes: Parallelism Monotonic, Idling, Limited Gang, and Limited Slack Reclaiming. Additionally, we study the predictability of our schedulers: we show that Gang FJP schedulers are not predictable and we identify several sub-classes which are actually predictable. Moreover, we extend the definition of rigid, moldable and malleable jobs to recurrent tasks.


Semi-Partitioned Hard Real-Time Scheduling with Restricted Migrations upon Identical Multiprocessor Platforms

Abstract: Algorithms based on semi-partitioned scheduling have been proposed as a viable alternative between the two extreme ones based on global and partitioned scheduling. In particular, allowing migration to occur only for few tasks which cannot be assigned to any individual processor, while most tasks are assigned to specific processors, considerably reduces the runtime overhead compared to global scheduling on the one hand, and improve both the schedulability and the system utilization factor compared to partitioned scheduling on the other hand. In this paper, we address the preemptive scheduling problem of hard real-time systems composed of sporadic constrained-deadline tasks upon identical multiprocessor platforms. We propose a new algorithm and a scheduling paradigm based on the concept of semi-partitioned scheduling with restricted migrations in which jobs are not allowed to migrate, but two subsequent jobs of a task can be assigned to different processors by following a periodic strategy.


A Study on Performance Analysis Tools for Applications Running on Large Distributed Systems

Abstract: The evolution of distributed architectures and programming paradigms for performance-oriented program development, challenge the state-of-the-art technology for performance tools. The area of high performance computing is rapidly expanding from single parallel systems to clusters and grids of heterogeneous sequential and parallel systems. Performance analysis and tuning applications is becoming crucial because it is hardly possible to otherwise achieve the optimum performance of any application. The objective of this paper is to study the state-of-the-art technology of the existing performance tools for distributed systems. The paper surveys some representative tools from different aspects in order to highlight the approaches and technologies used by them.


Monotonic Mappings Invariant Linearisation of Finite Posets

Abstract: In this paper we describe a novel a procedure to build a linear order from an arbitrary poset which (i) preserves the original ordering and (ii) allows to extend monotonic and antitonic mappings defined over the original poset to monotonic and antitonic mappings over the new linear poset.


A Markov Chain Model for the Analysis of Round-Robin Scheduling Scheme

Abstract: In the literature of Round-Robin scheduling scheme, each job is processed, one after the another after giving a fix quantum. In case of First-come first-served, each process is executed, if the previously arrived processed is completed. Both these scheduling schemes are used in this paper as its special cases. A Markov chain model is used to compare several scheduling schemes of the class. An index measure is defined to compare the model based efficiency of different scheduling schemes. One scheduling scheme which is the mixture of FIFO and round robin is found efficient in terms of model based study. The system simulation procedure is used to derive the conclusion of the content


Experimentation for Packet Loss on MSP430 and nRF24L01 Based Wireless Sensor Network

Abstract: In this paper,a new design of wireless sensor network (WSN)node is discussed which is based on components with ultra low power.We ha e de eloped a Low cost and low power WSN Node using MSP430 and nRF24L01.The architectural circuit details are presented.This architecture fulfils the requirements like low cost,low power,compact size and self organization.Various tests are carried out to test the performance of the nRF24L01 module.The packet loss,free Space loss (FSL)and battery lifetime calculations are described.These test results will help the researchers to build new applications using abo e node and to work efficiently with nRF24L01.


Enhancing the Authentication of Bank Cheque Signatures by Implementing Automated System Using Recurrent Neural Network

Abstract: The associatie memory feature of the Hopfield type recurrent neural network is used for the pattern storage and pattern authentication.This paper outlines an optimization relaxation approach for signature verification based on the Hopfield neural network (HNN)which is a recurrent network.The standard sample signature of the customer is cross matched with the one supplied on the Cheque.The difference percentage is obtained by calculating the different pixels in both the images.The network topology is built so that each pixel in the difference image is a neuron in the network.Each neuron is categorized by its states,which in turn signifies that if the particular pixel is changed.The network converges to unwavering condition based on the energy function which is derived in experiments.The Hopfield's model allows each node to take on two binary state values (changed/unchanged)for each pixel.The performance of the proposed technique is evaluated by applying it in various binary and gray scale images.This paper contributes in finding an automated scheme for verification of authentic signature on bank Cheques.The derived energy function allows a trade off between the influence of its neighborhood and its own criterion.This device is able to recall as well as complete partially specified inputs.The network is trained via a storage prescription that forces stable states to correspond to (local)minima of a network "energy" function.


Network Intrusion Detection Using FP Tree Rules

Abstract: In the faceless world of the Internet,online fraud is one of the greatest reasons of loss for web merchants.Advanced solutions are needed to protect e businesses from the constant problems of fraud.Many popular fraud detection algorithms require supervised training,which needs human intervention to prepare training cases.Since it is quite often for an online transaction database to ha e Terabyte level storage,human investigation to identify fraudulent transactions is very costly.This paper describes the automatic design of user profiling method for the purpose of fraud detection.We use a FP (Frequent Pattern) Tree rule learning algorithm to adaptively profile legitimate customer behavior in a transaction database.Then the incoming transactions are compared against the user profile to uncover the anomalies The anomaly outputs are used as input to an accumulation system for combining evidence to generate high confidence fraud alert value. Favorable experimental results are presented.


Real Time and Energy Efficient Transport Protocol for Wireless Sensor Networks

Abstract: Reliable transport protocols such as TCP are tuned to perform well in traditional networks where packet losses occur mostly because of congestion. Many applications of wireless sensor networks are useful only when connected to an external network. Previous research on transport layer protocols for sensor networks has focused on designing protocols specifically targeted for sensor networks. The deployment of TCP/IP in sensor networks would, however, enable direct connection between the sensor network and external TCP/IP networks. In this paper we focus on the performance of TCP in the context of wireless sensor networks. TCP is known to exhibit poor performance in wireless environments, both in terms of throughput and energy efficiency. To overcome these problems we introduce a mechanism called TCP Segment Caching .We show by simulation that TCP Segment Caching significantly improves TCP Performance so that TCP can be useful e en in wireless sensor


The Study State Analysis of Tandem Queue with Blocking and Feedback

Abstract: Computer system models provide detailed answer to system performance.In this paper a two stage tandem network system with Blocking and Feedback is considered and it performance has been analyzed by spectral expansion method.The study state system with balance equations has been discussed.


Customized way of Resource Discovery in a Campus Grid

Abstract: Campus Grid computing involves heterogeneous resources of an organization working in collaboration to sol e the problems that cannot be addressed by a single resource. However, basic problem for Campus Grid users is how to disco er the best resources required for the particular type of a job. There are various approaches using which Grid Discovery can be performed. This paper pro ides the grid resource discovery solutions for Campus Grid using Globus Toolkit which will enable us to customize the resource information according to the requirements based on the jobs to be run on the Campus Grid and present it in our own format. Here we propose building up our own service on top of globus MDS in order to process the information provided by MDS and use it in our Campus Grid Portal.


Information Delivery System through Bluetooth in Ubiquitous Networks

Abstract: computers into the real world, to serve humans where the ubiquitous network is the underneath infrastructure. In order to provide ubiquitous services (u-Service) which deliver useful information to service users without human intervention, this paper implements a proactive information delivery system using Bluetooth technology. Bluetooth is a lowpowered networking service that supports several protocol profiles, most importantly file transfer.Combined together, ubiquitous computing and Bluetooth ha e the potential to furnish ubiquitous solutions (u-Solutions) that are efficient, employ simplified design characteristics, and collaboratively perform functions they are otherwise not capable. Thus, this paper first addresses the current Bluetooth technology. Then, it suggests and develops the proactive information delivery system utilizing Bluetooth and ubiquitous computing network concepts. The proactive information delivery system can be used in many ubiquitous applications such as ubiquitous commerce (u-Commerce) and ubiquitous education (u- Education)


Image Segmentation Using Weak Shape Priors

Abstract: The problem of image segmentation is known to become particularly challenging in the case of partial occlusion of the object(s) of interest, background clutter, and the presence of strong noise. To overcome this problem, the present paper introduces a novel approach segmentation through the use of "weak" shape priors. Specifically, in the proposed method, an segmenting active contour is constrained to converge to a configuration at which its geometric parameters attain their empirical probability densities closely matching the corresponding model densities that are learned based on training samples. It is shown through numerical experiments that the proposed shape modeling can be regarded as "weak" in the sense that it minimally influences the segmentation, which is allowed to be dominated by data-related forces. On the other hand, the priors provide sufficient constraints to regularize the convergence of segmentation, while requiring substantially smaller training sets to yield less biased results as compared to the case of PCA-based regularization methods. The main advantages of the proposed technique over some existing alternatives is demonstrated in a series of experiments.


SPIM Architecture for MVC based Web Applications

Abstract: The Model / View / Controller design pattern divides an application environment into three components to handle the user-interactions, computations and output respectively. This separation greatly favors architectural reusability. The pattern works well in the case of single-address space and not proven to be efficient for web applications involving multiple address spaces. Web applications force the designers to decide which of the components of the pattern are to be partitioned between the server and client(s) before the design phase commences. For any rapidly growing web application, it is very difficult to incorporate future changes in policies related to partitioning. One solution to this problem is to duplicate the Model and controller components at both server and client(s). However, this may add further problems like delayed data fetch, security and scalability issues. In order to overcome this, a new architecture SPIM has been proposed that deals with the partitioning problem in an alternative way. SPIM shows tremendous improvements in performance when compared with a similar architecture.


From RESTful Services to RDF: Connecting the Web and the Semantic Web

Abstract: RESTful services on the Web expose information through retrievable resource representations that represent self-describing descriptions of resources, and through the way how these resources are interlinked through the hyperlinks that can be found in those representations. This basic design of RESTful services means that for extracting the most useful information from a service, it is necessary to understand a service's representations, which means both the semantics in terms of describing a resource, and also its semantics in terms of describing its linkage with other resources. Based on the Resource Linking Language (ReLL), this paper describes a framework for how RESTful services can be described, and how these descriptions can then be used to harvest information from these services. Building on this framework, a layered model of RESTful service semantics allows to represent a service's information in RDF/OWL. Because REST is based on the linkage between resources, the same model can be used for aggregating and interlinking multiple services for extracting RDF data from sets of RESTful services.


Partially Ordered Two-way B\"uchi Automata

Abstract: We introduce partially ordered two-way B\"uchi automata and characterize their expressive power in terms of fragments of first-order logic FO[<]. Partially ordered two-way B\"uchi automata are B\"uchi automata which can change the direction in which the input is processed with the constraint that whenever a state is left, it is never re-entered again. Nondeterministic partially ordered two-way B\"uchi automata coincide with the first-order fragment Sigma2. Our main contribution is that deterministic partially ordered two-way B\"uchi automata are expressively complete for the first-order fragment Delta2. As an intermediate step, we show that deterministic partially ordered two-way B\"uchi automata are effectively closed under Boolean operations. A small model property yields coNP-completeness of the emptiness problem and the inclusion problem for deterministic partially ordered two-way B\"uchi automata.


Attack--Defense Trees and Two-Player Binary Zero-Sum Extensive Form Games Are Equivalent - Technical Report with Proofs

Abstract: Attack--defense trees are used to describe security weaknesses of a system and possible countermeasures. In this paper, the connection between attack--defense trees and game theory is made explicit. We show that attack--defense trees and binary zero-sum two-player extensive form games have equivalent expressive power when considering satisfiability, in the sense that they can be converted into each other while preserving their outcome and their internal structure.


Penalized K-Nearest-Neighbor-Graph Based Metrics for Clustering

Abstract: A difficult problem in clustering is how to handle data with a manifold structure, i.e. data that is not shaped in the form of compact clouds of points, forming arbitrary shapes or paths embedded in a high-dimensional space. In this work we introduce the Penalized k-Nearest-Neighbor-Graph (PKNNG) based metric, a new tool for evaluating distances in such cases. The new metric can be used in combination with most clustering algorithms. The PKNNG metric is based on a two-step procedure: first it constructs the k-Nearest-Neighbor-Graph of the dataset of interest using a low k-value and then it adds edges with an exponentially penalized weight for connecting the sub-graphs produced by the first step. We discuss several possible schemes for connecting the different sub-graphs. We use three artificial datasets in four different embedding situations to evaluate the behavior of the new metric, including a comparison among different clustering methods. We also evaluate the new metric in a real world application, clustering the MNIST digits dataset. In all cases the PKNNG metric shows promising clustering results.


Global Optimization for Value Function Approximation

Abstract: Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bilinear programming formulation of value function approximation, which employs global optimization. The formulation provides strong a priori guarantees on both robust and expected policy loss by minimizing specific norms of the Bellman residual. Solving a bilinear program optimally is NP-hard, but this is unavoidable because the Bellman-residual minimization itself is NP-hard. We describe and analyze both optimal and approximate algorithms for solving bilinear programs. The analysis shows that this algorithm offers a convergent generalization of approximate policy iteration. We also briefly analyze the behavior of bilinear programming algorithms under incomplete samples. Finally, we demonstrate that the proposed approach can consistently minimize the Bellman residual on simple benchmark problems.


Controlling program extraction in Elementary Linear Logic

Abstract: We present an adaptation, based on program extraction in elementary linear logic, of Krivine & Leivant's system FA_2. This system allows to write higher-order equations in order to specify the computational content of extracted programs. The user can then prove a generic formula, using these equations as axioms, whose proof can be extracted into programs that normalize in elementary time and satisfy the specifications. Finally, we show that every elementary recursive functions can be implemented in this system.


Performance Analysis of QoS in PMP Mode WiMax Networks

Abstract: IEEE 802.16 standard supports two different topologies: point to multipoint (PMP) and Mesh. In this paper, a QoS mechanism for point to multipoint of IEEE 802.16 and BS scheduler for PMP Mode is proposed. This paper also describes quality of service over WiMAX networks. Average WiMAX delay, Average WiMAX load and Average WiMAX throughput at base station is analyzed and compared by applying different scheduler at Base station and at fixed nodes.


Motion Detection Notification System by Short Messaging Service Using Network Camera and Global System for Mobile Modem

Abstract: As the technology rapidly grows, the trend is clear that the use of mobile devices is gain an attention nowadays, thus designing a system by integrating it with notification feature is becoming an important aspect especially in tracking and monitoring system. Conventional security surveillance systems require the constant attention from the user, to monitor the location concurrently. In order to reduce the cost of computing power and advance technology of mobile phone in widespread acceptance of the Internet as a viable communication medium, this paper is aimed to design a low cost web-based system as a platform to view the image captured. When the network camera detects any movement from the intruders, it automatically captures the image and sends it to the database of the web-based directly by the network through File Transfer Protocol (FTP). The camera is attached through an Ethernet connection and power source. Therefore, the camera can be viewed from either standard Web browser or cell phone. Nowadays, when a security camera is installed, user is notified as long as the camera is switched on since any slight movement requires the attention of the supervisor. The utility of the system has proven theoretically. This system will also notify the user by sending a notification through Short Messages Services (SMS).


Virtual On-demand Test Lab using Cloud based Architecture

Abstract: Over a past few decades, VM's or Virtual machines have sort of gained a lot of momentum, especially for large scale enterprises where the need for resource optimization & power save is humongous, without compromising with performance or quality. They are a perfect environment to experiment with new applications/technologies in a completely secure and closed environment. This paper discusses how the VM technology can be leveraged to solve day to day requirement of an odd hundreds or thousands of people, organization-wide, with new computational resources using a cluster of heterogeneous low or high-end machines, independent of underlying OS, thereby maximizing resource utilization. It takes into account both opensource (like VirtualBox) & other proprietary technologies (like VMWare Workstations) available till date to propose a viable solution using cloud computing concept. The ease of scalability to multiple folds for optimizing performance & catering to an even larger set are some of the salient features of this approach. Using the snapshot feature, the state of any VM instance could be saved & served back again on request. Now, this implementation is also served by VMWare ESX server but again it's a costly solution & requires dedicated high-end machines to work with.


An Effective Fingerprint Verification Technique

Abstract: This paper presents an effective method for fingerprint verification based on a data mining technique called minutiae clustering and a graph-theoretic approach to analyze the process of fingerprint comparison to give a feature space representation of minutiae and to produce a lower bound on the number of detectably distinct fingerprints. The method also proving the invariance of each individual fingerprint by using both the topological behavior of the minutiae graph and also using a distance measure called Hausdorff distance.The method provides a graph based index generation mechanism of fingerprint biometric data. The self-organizing map neural network is also used for classifying the fingerprints.


Robust PI Control Design Using Particle Swarm Optimization

Abstract: This paper presents a set of robust PI tuning formulae for a first order plus dead time process using particle swarm optimization. Also, tuning formulae for an integrating process with dead time, which is a special case of a first order plus dead time process, is given. The design problem considers three essential requirements of control problems, namely load disturbance rejection, setpoint regulation and robustness of closed-loop system against model uncertainties. The primary design goal is to optimize load disturbance rejection. Robustness is guaranteed by requiring that the maximum sensitivity is less than or equal to a specified value. In the first step, PI controller parameters are determined such that the IAE criterion to a load disturbance step is minimized and the robustness constraint on maximum sensitivity is satisfied. Using a structure with two degrees of freedom which introduces an extra parameter, the setpoint weight, good setpoint regulation is achieved in the second step. The main advantage of the proposed method is its simplicity. Once the equivalent first order plus dead time model is determined, the PI parameters are explicitly given by a set of tuning formulae. In order to show the performance and effectiveness of the proposed tuning formulae, they are applied to three simulation examples.


A Metaheuristic Approach for IT Projects Portfolio Optimization

Abstract: Optimal selection of interdependent IT Projects for implementation in multi periods has been challenging in the framework of real option valuation. This paper presents a mathematical optimization model for multi-stage portfolio of IT projects. The model optimizes the value of the portfolio within a given budgetary and sequencing constraints for each period. These sequencing constraints are due to time wise interdependencies among projects. A Metaheuristic approach is well suited for solving this kind of a problem definition and in this paper a genetic algorithm model has been proposed for the solution. This optimization model and solution approach can help IT managers taking optimal funding decision for projects prioritization in multiple sequential periods. The model also gives flexibility to the managers to generate alternative portfolio by changing the maximum and minimum number of projects to be implemented in each sequential period.


Denial of Service Attack: Analysis of Network Traffic Anormaly using Queuing Theory

Abstract: Denial-of-service (DOS) attacks increasingly gained reputation over the past few years. As the Internet becomes more ubiquitous, the threat of the denial-of-service attacks becomes more realistic and important for individuals, businesses, governmental organizations, and even countries. There is intensive need to detect an attack in progress as soon as possible. The efficiency of diagnosing the DOS attack using concepts of queuing theory and performance parameter of the system has been investigated in the present work, as the servers definitely have some mechanisms to store and process the requests. Utilizing this concept of queuing theory, the collection of data patterns were generated. With the performance parameter of the system, the analysis of the data pattern had been made to diagnose the network anomaly. Performance analysis and results show the accuracy of the proposed scheme in detecting anomalies.


Offline Arabic Handwriting Recognition Using Artificial Neural Network

Abstract: The ambition of a character recognition system is to transform a text document typed on paper into a digital format that can be manipulated by word processor software Unlike other languages, Arabic has unique features, while other language doesn't have, from this language these are seven or eight language such as ordo, jewie and Persian writing, Arabic has twenty eight letters, each of which can be linked in three different ways or separated depending on the case. The difficulty of the Arabic handwriting recognition is that, the accuracy of the character recognition which affects on the accuracy of the word recognition, in additional there is also two or three from for each character, the suggested solution by using artificial neural network can solve the problem and overcome the difficulty of Arabic handwriting recognition.


High Speed Reconfigurable FFT Design by Vedic Mathematics

Abstract: The Fast Fourier Transform (FFT) is a computationally intensive digital signal processing (DSP) function widely used in applications such as imaging, software-defined radio, wireless communication, instrumentation. In this paper, a reconfigurable FFT design using Vedic multiplier with high speed and small area is presented. Urdhava Triyakbhyam algorithm of ancient Indian Vedic Mathematics is utilized to improve its efficiency. In the proposed architecture, the 4x4 bit multiplication operation is fragmented reconfigurable FFT modules. The 4x4 multiplication modules are implemented using small 2x2bit multipliers. Reconfigurability at run time is provided for attaining power saving. The reconfigurable FFT has been designed, optimized and implemented on an FPGA based system. This reconfigurable FFT is having the high speed and small area as compared to the conventional FFT.


Component Interaction Graph: A new approach to test component composition

Abstract: The key factor of component based software development is component composition technology. A Component interaction graph is used to describe the interrelation of components. Drawing a complete component interaction graph (CIG) provides an objective basis and technical means for making the testing outline. Although many researches have focused on this subject, the quality of system that is composed of components has not been guaranteed. In this paper, a CIG is constructed from a state chart diagram and new test cases are generated to test the component composition.


An approach to find dynamic slice for C++ Program

Abstract: Object-oriented programming has been considered a most promising method in program development and maintenance. An important feature of object-oriented programs (OOPs) is their reusability which can be achieved through the inheritance of classes or reusable components.Dynamic program slicing is an effective technique for narrowing the errors to the relevant parts of a program when debugging. Given a slicing criterion, the dynamic slice contains only those statements that actually affect the variables in the slicing criterion. This paper proposes a method to dynamically slice object-oriented (00) programs based on dependence analysis. It uses the Control Dependency Graph for object program and other static information to reduce the information to be traced during program execution. In this paper we present a method to find the dynamic Slice of object oriented programs where we are finding the slices for object and in case of function overloading.


Effect of Distributed Shield Insertion on Crosstalk in Inductively Coupled VLSI Interconnects

Abstract: Crosstalk in VLSI interconnects is a major constrain in DSM and UDSM technology. Among various strategies followed for its minimization, shield insertion between Aggressor and Victim is one of the prominent options. This paper analyzes the extent of crosstalk in inductively coupled interconnects and minimizes the same through distributed shield insertion. Comparison is drawn between signal voltage and crosstalk voltage in three different conditions i.e. prior to shield insertion, after shield insertion and after additional ground tap insertion at shield terminal.


A Parallel Encryption Algorithm for Block Ciphers Based on Reversible Programmable Cellular Automata

Abstract: A Cellular Automata (CA) is a computing model of complex System using simple rule. In CA the problem space into number of cell and each cell can be one or several final state. Cells are affected by neighbours' to the simple rule. Cellular Automata are highly parallel and discrete dynamical systems, whose behaviour is completely specified in terms of a local relation. This paper deals with the Cellular Automata (CA) in cryptography for a class of Block Ciphers through a new block encryption algorithm based on Reversible Programmable Cellular Automata Theory. The proposed algorithm belongs to the class of symmetric key systems.


Fuzzy Modeling and Natural Language Processing for Panini's Sanskrit Grammar

Abstract: Indian languages have long history in World Natural languages. Panini was the first to define Grammar for Sanskrit language with about 4000 rules in fifth century. These rules contain uncertainty information. It is not possible to Computer processing of Sanskrit language with uncertain information. In this paper, fuzzy logic and fuzzy reasoning are proposed to deal to eliminate uncertain information for reasoning with Sanskrit grammar. The Sanskrit language processing is also discussed in this paper.


A Decentralized Approach for Service Discovery & Availability in P-Grids

Abstract: The widespread emergence of the Internet as a platform for electronic data distribution and the advent of structured information have revolutionized our ability to deliver information to any corner of the world. Although Service Oriented Architecture (SOA) is a paradigm for organizing and utilizing distributed capabilities that may be under the control of different ownership domains and implemented using various technology stacks and every organization may not be geared up for this. To harness the various software / service resources placed on various systems, we have proposed and implemented a model that is able to establish discovery and sharing in load balanced P-grid environment. The experimental results show that the proposed approach has dramatically lowered the network traffic (nearly negligible), while achieving load balancing in P2P grid systems. Our model is able to support discovery and sharing of resources also.


A Complexity measure based on Requirement Engineering Document

Abstract: Research shows, that the major issue in development of quality software is precise estimation. Further this estimation depends upon the degree of intricacy inherent in the software i.e. complexity. This paper attempts to empirically demonstrate the proposed complexity which is based on IEEE Requirement Engineering document. It is said that a high quality SRS is pre requisite for high quality software. Requirement Engineering document (SRS) is a specification for a particular software product, program or set of program that performs some certain functions for a specific environment. The various complexity measure given so far are based on Code and Cognitive metrics value of software, which are code based. So these metrics provide no leverage to the developer of the code. Considering the shortcoming of code based approaches, the proposed approach identifies complexity of software immediately after freezing the requirement in SDLC process. The proposed complexity measure compares well with established complexity measures. Finally the trend can be validated with the result of proposed measure. Ultimately, Requirement based complexity measure can be used to understand the complexity of proposed software much before the actual implementation of design thus saving on cost and manpower wastage.


Outrepasser les limites des techniques classiques de Prise d'Empreintes grace aux Reseaux de Neurones

Abstract: We present an application of Artificial Intelligence techniques to the field of Information Security. The problem of remote Operating System (OS) Detection, also called OS Fingerprinting, is a crucial step of the penetration testing process, since the attacker (hacker or security professional) needs to know the OS of the target host in order to choose the exploits that he will use. OS Detection is accomplished by passively sniffing network packets and actively sending test packets to the target host, to study specific variations in the host responses revealing information about its operating system. The first fingerprinting implementations were based on the analysis of differences between TCP/IP stack implementations. The next generation focused the analysis on application layer data such as the DCE RPC endpoint information. Even though more information was analyzed, some variation of the "best fit" algorithm was still used to interpret this new information. Our new approach involves an analysis of the composition of the information collected during the OS identification process to identify key elements and their relations. To implement this approach, we have developed tools using Neural Networks and techniques from the field of Statistics. These tools have been successfully integrated in a commercial software (Core Impact).


Internalized realizability in pure type systems

Abstract: Let P be any pure type system, we are going to show how we can extend P into a PTS P' which will be used as a proof system whose formulas express properties about sets of terms of P. We will show that P' is strongly normalizable if and only if P is. Given a term t in P and a formula F in P', P' is expressive enough to construct a formula "t ||- F" that is interpreted as "t is a realizer of F". We then prove the following adequacy theorem: if F is provable then by projecting its proof back to a term t in P we obtain a proof that "t ||- F".


Fast Incremental and Personalized PageRank

Abstract: In this paper, we analyze the efficiency of Monte Carlo methods for incremental computation of PageRank, personalized PageRank, and similar random walk based methods (with focus on SALSA), on large-scale dynamically evolving social networks. We assume that the graph of friendships is stored in distributed shared memory, as is the case for large social networks such as Twitter. For global PageRank, we assume that the social network has $n$ nodes, and $m$ adversarially chosen edges arrive in a random order. We show that with a reset probability of $\epsilon$, the total work needed to maintain an accurate estimate (using the Monte Carlo method) of the PageRank of every node at all times is $O(\frac{n\ln m}{\epsilon^{2}})$. This is significantly better than all known bounds for incremental PageRank. For instance, if we naively recompute the PageRanks as each edge arrives, the simple power iteration method needs $\Omega(\frac{m^2}{\ln(1/(1-\epsilon))})$ total time and the Monte Carlo method needs $O(mn/\epsilon)$ total time; both are prohibitively expensive. Furthermore, we also show that we can handle deletions equally efficiently. We then study the computation of the top $k$ personalized PageRanks starting from a seed node, assuming that personalized PageRanks follow a power-law with exponent $\alpha < 1$. We show that if we store $R>q\ln n$ random walks starting from every node for large enough constant $q$ (using the approach outlined for global PageRank), then the expected number of calls made to the distributed social network database is $O(k/(R^{(1-\alpha)/\alpha}))$. We also present experimental results from the social networking site, Twitter, verifying our assumptions and analyses. The overall result is that this algorithm is fast enough for real-time queries over a dynamic social network.


The Power of Nondeterminism in Self-Assembly

Abstract: We investigate the role of nondeterminism in Winfree's abstract Tile Assembly Model (aTAM), which was conceived to model artificial molecular self-assembling systems constructed from DNA. Of particular practical importance is to find tile systems that minimize resources such as the number of distinct tile types, each of which corresponds to a set of DNA strands that must be custom-synthesized in actual molecular implementations of the aTAM. We seek to identify to what extent the use of nondeterminism in tile systems affects the resources required by such molecular shape-building algorithms. We first show a "molecular computability theoretic" result: there is an infinite shape S that is uniquely assembled by a tile system but not by any deterministic tile system. We then show an analogous phenomenon in the finitary "molecular complexity theoretic" case: there is a finite shape S that is uniquely assembled by a tile system with c tile types, but every deterministic tile system that uniquely assembles S has more than c tile types. In fact we extend the technique to derive a stronger (classical complexity theoretic) result, showing that the problem of finding the minimum number of tile types that uniquely assemble a given finite shape is Sigma-P-2-complete. In contrast, the problem of finding the minimum number of deterministic tile types that uniquely assemble a shape was shown to be NP-complete by Adleman, Cheng, Goel, Huang, Kempe, Moisset de Espan\'es, and Rothemund (Combinatorial Optimization Problems in Self-Assembly, STOC 2002). The conclusion is that nondeterminism confers extra power to assemble a shape from a small tile system, but unless the polynomial hierarchy collapses, it is computationally more difficult to exploit this power by finding the size of the smallest tile system, compared to finding the size of the smallest deterministic tile system.


Approximated Structured Prediction for Learning Large Scale Graphical Models

Abstract: This manuscripts contains the proofs for "A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction".


How to generate an object under an ordinary Boltzmann distribution via an exponential Boltzmann sampler

Abstract: This short note presents an efficient way to derive from an exponential Boltzmann sampler a ordinary Boltzmann sampler


Instantiation of SMT problems modulo Integers

Abstract: Many decision procedures for SMT problems rely more or less implicitly on an instantiation of the axioms of the theories under consideration, and differ by making use of the additional properties of each theory, in order to increase efficiency. We present a new technique for devising complete instantiation schemes on SMT problems over a combination of linear arithmetic with another theory T. The method consists in first instantiating the arithmetic part of the formula, and then getting rid of the remaining variables in the problem by using an instantiation strategy which is complete for T. We provide examples evidencing that not only is this technique generic (in the sense that it applies to a wide range of theories) but it is also efficient, even compared to state-of-the-art instantiation schemes for specific theories.


Modularity of Convergence and Strong Convergence in Infinitary Rewriting

Abstract: Properties of Term Rewriting Systems are called modular iff they are preserved under (and reflected by) disjoint union, i.e. when combining two Term Rewriting Systems with disjoint signatures. Convergence is the property of Infinitary Term Rewriting Systems that all reduction sequences converge to a limit. Strong Convergence requires in addition that redex positions in a reduction sequence move arbitrarily deep. In this paper it is shown that both Convergence and Strong Convergence are modular properties of non-collapsing Infinitary Term Rewriting Systems, provided (for convergence) that the term metrics are granular. This generalises known modularity results beyond metric \infty.


Two-Timescale Learning Using Idiotypic Behaviour Mediation For A Navigating Mobile Robot

Abstract: A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile-robot navigation problems is presented and tested in both the real and virtual domains. The LTL phase consists of rapid simulations that use a Genetic Algorithm to derive diverse sets of behaviours, encoded as variable sets of attributes, and the STL phase is an idiotypic Artificial Immune System. Results from the LTL phase show that sets of behaviours develop very rapidly, and significantly greater diversity is obtained when multiple autonomous populations are used, rather than a single one. The architecture is assessed under various scenarios, including removal of the LTL phase and switching off the idiotypic mechanism in the STL phase. The comparisons provide substantial evidence that the best option is the inclusion of both the LTL phase and the idiotypic system. In addition, this paper shows that structurally different environments can be used for the two phases without compromising transferability.


Approximation Algorithm for Line Segment Coverage for Wireless Sensor Network

Abstract: The coverage problem in wireless sensor networks deals with the problem of covering a region or parts of it with sensors. In this paper, we address the problem of covering a set of line segments in sensor networks. A line segment ` is said to be covered if it intersects the sensing regions of at least one sensor distributed in that region. We show that the problem of finding the minimum number of sensors needed to cover each member in a given set of line segments in a rectangular area is NP-hard. Next, we propose a constant factor approximation algorithm for the problem of covering a set of axis-parallel line segments. We also show that a PTAS exists for this problem.


Extended core and choosability of a graph

Abstract: A graph $G$ is $(a,b)$-choosable if for any color list of size $a$ associated with each vertices, one can choose a subset of $b$ colors such that adjacent vertices are colored with disjoint color sets. This paper shows an equivalence between the $(a,b)$-choosability of a graph and the $(a,b)$-choosability of one of its subgraphs called the extended core. As an application, this result allows to prove the $(5,2)$-choosability and $(7,3)$-colorability of triangle-free induced subgraphs of the triangular lattice.


Imitation in Large Games

Abstract: In games with a large number of players where players may have overlapping objectives, the analysis of stable outcomes typically depends on player types. A special case is when a large part of the player population consists of imitation types: that of players who imitate choice of other (optimizing) types. Game theorists typically study the evolution of such games in dynamical systems with imitation rules. In the setting of games of infinite duration on finite graphs with preference orderings on outcomes for player types, we explore the possibility of imitation as a viable strategy. In our setup, the optimising players play bounded memory strategies and the imitators play according to specifications given by automata. We present algorithmic results on the eventual survival of types.


Two-Domain DNA Strand Displacement

Abstract: We investigate the computing power of a restricted class of DNA strand displacement structures: those that are made of double strands with nicks (interruptions) in the top strand. To preserve this structural invariant, we impose restrictions on the single strands they interact with: we consider only two-domain single strands consisting of one toehold domain and one recognition domain. We study fork and join signal-processing gates based on these structures, and we show that these systems are amenable to formalization and to mechanical verification.


Universal Loop-Free Super-Stabilization

Abstract: We propose an univesal scheme to design loop-free and super-stabilizing protocols for constructing spanning trees optimizing any tree metrics (not only those that are isomorphic to a shortest path tree). Our scheme combines a novel super-stabilizing loop-free BFS with an existing self-stabilizing spanning tree that optimizes a given metric. The composition result preserves the best properties of both worlds: super-stabilization, loop-freedom, and optimization of the original metric without any stabilization time penalty. As case study we apply our composition mechanism to two well known metric-dependent spanning trees: the maximum-flow tree and the minimum degree spanning tree.


A hands-on Assessment of Transport Protocols with Lower than Best Effort Priority

Abstract: Last year, the official BitTorrent client switched to LEDBAT, a new congestion control algorithm targeting a lower-than Best Effort transport service. In this paper, we study this new protocol through packet-level simulations, with a special focus on a performance comparison with other lower-than Best Effort protocols such as TCP-LP and TCP-NICE: our aim is indeed to quantify and relatively weight the level of Low-priority provided by such protocols. Our results show that LEDBAT transport generally achieves the lowest possible level of priority, with the default configurations of TCP-NICE and TCP-LP representing increasing levels of aggressiveness. In addition, we perform a careful sensitivity analysis of LEDBAT performance, by tuning its main parameters in both inter-protocol (against TCP) and intra-protocol (against LEDBAT itself) scenarios. In the inter-protocol case, although in case of misconfiguration LEDBAT competes as aggressively as TCP, however we show that it is not possible to achieve an arbitrary level of low-priority by merely tuning its parameters. In the intra-protocol case, we show that coexistence of legacy flows with slightly dissimilar settings, or experiencing different network conditions, can result in significant unfairness.


The quest for LEDBAT fairness

Abstract: BitTorrent developers have recently introduced a new application layer congestion control algorithm based on UDP framing at transport layer and currently under definition at the IETF LEDBAT Working Group. LEDBAT is a delay-based protocol which aims at offering a "lower than Best Effort" data transfer service, with a lower priority with respect to elastic TCP and interactive traffic (e.g., VoIP, game). However, in its current specification, LEDBAT is affected by a late-comer advantage: indeed the last flow arriving at the bottleneck is more aggressive due to a wrong estimation of the base delay and finally takes over all resources. In this work, we study several solutions to the late-comer problem by means of packet level simulations and simple analysis: in the investigation process, we individuate the root cause for LEDBAT unfairness and propose effective countermeasures.


Bounded Search Tree Algorithms for Parameterized Cograph Deletion: Efficient Branching Rules by Exploiting Structures of Special Graph Classes

Abstract: Many fixed-parameter tractable algorithms using a bounded search tree have been repeatedly improved, often by describing a larger number of branching rules involving an increasingly complex case analysis. We introduce a novel and general search strategy that branches on the forbidden subgraphs of a graph class relaxation. By using the class of $P_4$-sparse graphs as the relaxed graph class, we obtain efficient bounded search tree algorithms for several parameterized deletion problems. We give the first non-trivial bounded search tree algorithms for the cograph edge-deletion problem and the trivially perfect edge-deletion problems. For the cograph vertex deletion problem, a refined analysis of the runtime of our simple bounded search algorithm gives a faster exponential factor than those algorithms designed with the help of complicated case distinctions and non-trivial running time analysis [21] and computer-aided branching rules [11].


A General Framework for Equivalences in Answer-Set Programming by Countermodels in the Logic of Here-and-There

Abstract: Different notions of equivalence, such as the prominent notions of strong and uniform equivalence, have been studied in Answer-Set Programming, mainly for the purpose of identifying programs that can serve as substitutes without altering the semantics, for instance in program optimization. Such semantic comparisons are usually characterized by various selections of models in the logic of Here-and-There (HT). For uniform equivalence however, correct characterizations in terms of HT-models can only be obtained for finite theories, respectively programs. In this article, we show that a selection of countermodels in HT captures uniform equivalence also for infinite theories. This result is turned into coherent characterizations of the different notions of equivalence by countermodels, as well as by a mixture of HT-models and countermodels (so-called equivalence interpretations). Moreover, we generalize the so-called notion of relativized hyperequivalence for programs to propositional theories, and apply the same methodology in order to obtain a semantic characterization which is amenable to infinite settings. This allows for a lifting of the results to first-order theories under a very general semantics given in terms of a quantified version of HT. We thus obtain a general framework for the study of various notions of equivalence for theories under answer-set semantics. Moreover, we prove an expedient property that allows for a simplified treatment of extended signatures, and provide further results for non-ground logic programs. In particular, uniform equivalence coincides under open and ordinary answer-set semantics, and for finite non-ground programs under these semantics, also the usual characterization of uniform equivalence in terms of maximal and total HT-models of the grounding is correct, even for infinite domains, when corresponding ground programs are infinite.


Satisfiability Thresholds for k-CNF Formula with Bounded Variable Intersections

Abstract: We determine the thresholds for the number of variables, number of clauses, number of clause intersection pairs and the maximum clause degree of a k-CNF formula that guarantees satisfiability under the assumption that every two clauses share at most $\alpha$ variables. More formally, we call these formulas $\alpha$-intersecting and define, for example, a threshold $\mu_i(k,\alpha)$ for the number of clause intersection pairs $i$, such that every $\alpha$-intersecting k-CNF formula in which at most $\mu_i(k,\alpha)$ pairs of clauses share a variable is satisfiable and there exists an unsatisfiable $\alpha$-intersecting k-CNF formula with $\mu_m(k,\alpha)$ such intersections. We provide a lower bound for these thresholds based on the Lovasz Local Lemma and a nearly matching upper bound by constructing an unsatisfiable k-CNF to show that $\mu_i(k,\alpha) = \tilde{\Theta}(2^{k(2+1/\alpha)})$. Similar thresholds are determined for the number of variables ($\mu_n = \tilde{\Theta}(2^{k/\alpha})$) and the number of clauses ($\mu_m = \tilde{\Theta}(2^{k(1+\frac{1}{\alpha})})$) (see [Scheder08] for an earlier but independent report on this threshold). Our upper bound construction gives a family of unsatisfiable formula that achieve all four thresholds simultaneously.


Extension of Wirtinger's Calculus to Reproducing Kernel Hilbert Spaces and the Complex Kernel LMS

Abstract: Over the last decade, kernel methods for nonlinear processing have successfully been used in the machine learning community. The primary mathematical tool employed in these methods is the notion of the Reproducing Kernel Hilbert Space. However, so far, the emphasis has been on batch techniques. It is only recently, that online techniques have been considered in the context of adaptive signal processing tasks. Moreover, these efforts have only been focussed on real valued data sequences. To the best of our knowledge, no adaptive kernel-based strategy has been developed, so far, for complex valued signals. Furthermore, although the real reproducing kernels are used in an increasing number of machine learning problems, complex kernels have not, yet, been used, in spite of their potential interest in applications that deal with complex signals, with Communications being a typical example. In this paper, we present a general framework to attack the problem of adaptive filtering of complex signals, using either real reproducing kernels, taking advantage of a technique called \textit{complexification} of real RKHSs, or complex reproducing kernels, highlighting the use of the complex gaussian kernel. In order to derive gradients of operators that need to be defined on the associated complex RKHSs, we employ the powerful tool of Wirtinger's Calculus, which has recently attracted attention in the signal processing community. To this end, in this paper, the notion of Wirtinger's calculus is extended, for the first time, to include complex RKHSs and use it to derive several realizations of the Complex Kernel Least-Mean-Square (CKLMS) algorithm. Experiments verify that the CKLMS offers significant performance improvements over several linear and nonlinear algorithms, when dealing with nonlinearities.


Products of Weighted Logic Programs

Abstract: Weighted logic programming, a generalization of bottom-up logic programming, is a well-suited framework for specifying dynamic programming algorithms. In this setting, proofs correspond to the algorithm's output space, such as a path through a graph or a grammatical derivation, and are given a real-valued score (often interpreted as a probability) that depends on the real weights of the base axioms used in the proof. The desired output is a function over all possible proofs, such as a sum of scores or an optimal score. We describe the PRODUCT transformation, which can merge two weighted logic programs into a new one. The resulting program optimizes a product of proof scores from the original programs, constituting a scoring function known in machine learning as a ``product of experts.'' Through the addition of intuitive constraining side conditions, we show that several important dynamic programming algorithms can be derived by applying PRODUCT to weighted logic programs corresponding to simpler weighted logic programs. In addition, we show how the computation of Kullback-Leibler divergence, an information-theoretic measure, can be interpreted using PRODUCT.


Concurrent Goal-Based Execution of Constraint Handling Rules

Abstract: (To appear in Theory and Practice of Logic Programming (TPLP)) We introduce a systematic, concurrent execution scheme for Constraint Handling Rules (CHR) based on a previously proposed sequential goal-based CHR semantics. We establish strong correspondence results to the abstract CHR semantics, thus guaranteeing that any answer in the concurrent, goal-based CHR semantics is reproducible in the abstract CHR semantics. Our work provides the foundation to obtain efficient, parallel CHR execution schemes.


Identifying Shapes Using Self-Assembly (extended abstract)

Abstract: In this paper, we introduce the following problem in the theory of algorithmic self-assembly: given an input shape as the seed of a tile-based self-assembly system, design a finite tile set that can, in some sense, uniquely identify whether or not the given input shape--drawn from a very general class of shapes--matches a particular target shape. We first study the complexity of correctly identifying squares. Then we investigate the complexity associated with the identification of a considerably more general class of non-square, hole-free shapes.


Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity

Abstract: A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm. A dual mathematical interpretation of the proposed framework with structured sparse estimation is described, which shows that the resulting piecewise linear estimate stabilizes the estimation when compared to traditional sparse inverse problem techniques. This interpretation also suggests an effective dictionary motivated initialization for the MAP-EM algorithm. We demonstrate that in a number of image inverse problems, including inpainting, zooming, and deblurring, the same algorithm produces either equal, often significantly better, or very small margin worse results than the best published ones, at a lower computational cost.


Sequences, Bent Functions and Jacobsthal sums

Abstract: The $p$-ary function $f(x)$ mapping $\mathrm{GF}(p^{4k})$ to $\mathrm{GF}(p)$ and given by $f(x)={\rm Tr}_{4k}\big(ax^d+bx^2\big)$ with $a,b\in\mathrm{GF}(p^{4k})$ and $d=p^{3k}+p^{2k}-p^k+1$ is studied with the respect to its exponential sum. In the case when either $a^{p^k(p^k+1)}\neq b^{p^k+1}$ or $a^2=b^d$ with $b\neq 0$, this sum is shown to be three-valued and the values are determined. For the remaining cases, the value of the exponential sum is expressed using Jacobsthal sums of order $p^k+1$. Finding the values and the distribution of those sums is a long-lasting open problem.


Classical and Intuitionistic Subexponential Logics are Equally Expressive

Abstract: It is standard to regard the intuitionistic restriction of a classical logic as increasing the expressivity of the logic because the classical logic can be adequately represented in the intuitionistic logic by double-negation, while the other direction has no truth-preserving propositional encodings. We show here that subexponential logic, which is a family of substructural refinements of classical logic, each parametric over a preorder over the subexponential connectives, does not suffer from this asymmetry if the preorder is systematically modified as part of the encoding. Precisely, we show a bijection between synthetic (i.e., focused) partial sequent derivations modulo a given encoding. Particular instances of our encoding for particular subexponential preorders give rise to both known and novel adequacy theorems for substructural logics.


Fast Self-Stabilizing Minimum Spanning Tree Construction

Abstract: We present a novel self-stabilizing algorithm for minimum spanning tree (MST) construction. The space complexity of our solution is $O(\log^2n)$ bits and it converges in $O(n^2)$ rounds. Thus, this algorithm improves the convergence time of all previously known self-stabilizing asynchronous MST algorithms by a multiplicative factor $\Theta(n)$, to the price of increasing the best known space complexity by a factor $O(\log n)$. The main ingredient used in our algorithm is the design, for the first time in self-stabilizing settings, of a labeling scheme for computing the nearest common ancestor with only $O(\log^2n)$ bits.


Leveraging shared caches for parallel temporal blocking of stencil codes on multicore processors and clusters

Abstract: Bandwidth-starved multicore chips have become ubiquitous. It is well known that the performance of stencil codes can be improved by temporal blocking, lessening the pressure on the memory interface. We introduce a new pipelined approach that makes explicit use of shared caches in multicore environments and minimizes synchronization and boundary overhead. Benchmark results are presented for three current x86-based microprocessors, showing clearly that our optimization works best on designs with high-speed shared caches and low memory bandwidth per core. We furthermore demonstrate that simple bandwidth-based performance models are inaccurate for this kind of algorithm and employ a more elaborate, synthetic modeling procedure. Finally we show that temporal blocking can be employed successfully in a hybrid shared/distributed-memory environment, albeit with limited benefit at strong scaling.


Abstract Fixpoint Computations with Numerical Acceleration Methods

Abstract: Static analysis by abstract interpretation aims at automatically proving properties of computer programs. To do this, an over-approximation of program semantics, defined as the least fixpoint of a system of semantic equations, must be computed. To enforce the convergence of this computation, widening operator is used but it may lead to coarse results. We propose a new method to accelerate the computation of this fixpoint by using standard techniques of numerical analysis. Our goal is to automatically and dynamically adapt the widening operator in order to maintain precision.


Tree-width of hypergraphs and surface duality

Abstract: In Graph Minors III, Robertson and Seymour write: "It seems that the tree-width of a planar graph and the tree-width of its geometric dual are approximately equal - indeed, we have convinced ourselves that they differ by at most one". They never gave a proof of this. In this paper, we prove a generalisation of this statement to embedding of hypergraphs on general surfaces, and we prove that our bound is tight.


H2O: An Autonomic, Resource-Aware Distributed Database System

Abstract: This paper presents the design of an autonomic, resource-aware distributed database which enables data to be backed up and shared without complex manual administration. The database, H2O, is designed to make use of unused resources on workstation machines. Creating and maintaining highly-available, replicated database systems can be difficult for untrained users, and costly for IT departments. H2O reduces the need for manual administration by autonomically replicating data and load-balancing across machines in an enterprise. Provisioning hardware to run a database system can be unnecessarily costly as most organizations already possess large quantities of idle resources in workstation machines. H2O is designed to utilize this unused capacity by using resource availability information to place data and plan queries over workstation machines that are already being used for other tasks. This paper discusses the requirements for such a system and presents the design and implementation of H2O.


Solving Functional Constraints by Variable Substitution

Abstract: Functional constraints and bi-functional constraints are an important constraint class in Constraint Programming (CP) systems, in particular for Constraint Logic Programming (CLP) systems. CP systems with finite domain constraints usually employ CSP-based solvers which use local consistency, for example, arc consistency. We introduce a new approach which is based instead on variable substitution. We obtain efficient algorithms for reducing systems involving functional and bi-functional constraints together with other non-functional constraints. It also solves globally any CSP where there exists a variable such that any other variable is reachable from it through a sequence of functional constraints. Our experiments on random problems show that variable elimination can significantly improve the efficiency of solving problems with functional constraints.


Contents of COMP5541 Winter 2010 Final UUIS SRS and SDD Reports

Abstract: This index covers the final course project reports for COMP5541 Winter 2010 at Concordia University, Montreal, Canada, Tools and Techniques for Software Engineering by 4 teams trying to capture the requirements, provide the design specification, configuration management, testing and quality assurance of their partial implementation of the Unified University Inventory System (UUIS) of an Imaginary University of Arctica (IUfA). Their results are posted here for comparative studies and analysis.


Quasirandom Load Balancing

Abstract: We propose a simple distributed algorithm for balancing indivisible tokens on graphs. The algorithm is completely deterministic, though it tries to imitate (and enhance) a random algorithm by keeping the accumulated rounding errors as small as possible. Our new algorithm surprisingly closely approximates the idealized process (where the tokens are divisible) on important network topologies. On d-dimensional torus graphs with n nodes it deviates from the idealized process only by an additive constant. In contrast to that, the randomized rounding approach of Friedrich and Sauerwald (2009) can deviate up to Omega(polylog(n)) and the deterministic algorithm of Rabani, Sinclair and Wanka (1998) has a deviation of Omega(n^{1/d}). This makes our quasirandom algorithm the first known algorithm for this setting which is optimal both in time and achieved smoothness. We further show that also on the hypercube our algorithm has a smaller deviation from the idealized process than the previous algorithms.


Optimal whitespace synchronization strategies

Abstract: The whitespace-discovery problem describes two parties, Alice and Bob, trying to establish a communication channel over one of a given large segment of whitespace channels. Subsets of the channels are occupied in each of the local environments surrounding Alice and Bob, as well as in the global environment between them (Eve). In the absence of a common clock for the two parties, the goal is to devise time-invariant (stationary) strategies minimizing the synchronization time. This emerged from recent applications in discovery of wireless devices. We model the problem as follows. There are $N$ channels, each of which is open (unoccupied) with probability $p_1,p_2,q$ independently for Alice, Bob and Eve respectively. Further assume that $N \gg 1/(p_1 p_2 q)$ to allow for sufficiently many open channels. Both Alice and Bob can detect which channels are locally open and every time-slot each of them chooses one such channel for an attempted sync. One aims for strategies that, with high probability over the environments, guarantee a shortest possible expected sync time depending only on the $p_i$'s and $q$. Here we provide a stationary strategy for Alice and Bob with a guaranteed expected sync time of $O(1 / (p_1 p_2 q^2))$ given that each party also has knowledge of $p_1,p_2,q$. When the parties are oblivious of these probabilities, analogous strategies incur a cost of a poly-log factor, i.e.\ $\tilde{O}(1 / (p_1 p_2 q^2))$. Furthermore, this performance guarantee is essentially optimal as we show that any stationary strategies of Alice and Bob have an expected sync time of at least $\Omega(1/(p_1 p_2 q^2))$.


A Review of the Energy Efficient and Secure Multicast Routing Protocols for Mobile Ad hoc Networks

Abstract: This paper presents a thorough survey of recent work addressing energy efficient multicast routing protocols and secure multicast routing protocols in Mobile Ad hoc Networks (MANETs). There are so many issues and solutions which witness the need of energy management and security in ad hoc wireless networks. The objective of a multicast routing protocol for MANETs is to support the propagation of data from a sender to all the receivers of a multicast group while trying to use the available bandwidth efficiently in the presence of frequent topology changes. Multicasting can improve the efficiency of the wireless link when sending multiple copies of messages by exploiting the inherent broadcast property of wireless transmission. Secure multicast routing plays a significant role in MANETs. However, offering energy efficient and secure multicast routing is a difficult and challenging task. In recent years, various multicast routing protocols have been proposed for MANETs. These protocols have distinguishing features and use different mechanisms


Optimal Constant-Time Approximation Algorithms and (Unconditional) Inapproximability Results for Every Bounded-Degree CSP

Abstract: Raghavendra (STOC 2008) gave an elegant and surprising result: if Khot's Unique Games Conjecture (STOC 2002) is true, then for every constraint satisfaction problem (CSP), the best approximation ratio is attained by a certain simple semidefinite programming and a rounding scheme for it. In this paper, we show that similar results hold for constant-time approximation algorithms in the bounded-degree model. Specifically, we present the followings: (i) For every CSP, we construct an oracle that serves an access, in constant time, to a nearly optimal solution to a basic LP relaxation of the CSP. (ii) Using the oracle, we give a constant-time rounding scheme that achieves an approximation ratio coincident with the integrality gap of the basic LP. (iii) Finally, we give a generic conversion from integrality gaps of basic LPs to hardness results. All of those results are \textit{unconditional}. Therefore, for every bounded-degree CSP, we give the best constant-time approximation algorithm among all. A CSP instance is called $\epsilon$-far from satisfiability if we must remove at least an $\epsilon$-fraction of constraints to make it satisfiable. A CSP is called testable if there is a constant-time algorithm that distinguishes satisfiable instances from $\epsilon$-far instances with probability at least $2/3$. Using the results above, we also derive, under a technical assumption, an equivalent condition under which a CSP is testable in the bounded-degree model.


Fault Tolerant Wireless Sensor MAC Protocol for Efficient Collision Avoidance

Abstract: In sensor networks communication by broadcast methods involves many hazards, especially collision. Several MAC layer protocols have been proposed to resolve the problem of collision namely ARBP, where the best achieved success rate is 90%. We hereby propose a MAC protocol which achieves a greater success rate (Success rate is defined as the percentage of delivered packets at the source reaching the destination successfully) by reducing the number of collisions, but by trading off the average propagation delay of transmission. Our proposed protocols are also shown to be more energy efficient in terms of energy dissipation per message delivery, compared to the currently existing protocol.


Enhancing QoS and QoE in IMS Enabled Next Generation Networks

Abstract: Managing network complexity, accommodating greater numbers of subscribers, improving coverage to support data services (e.g. email, video, and music downloads), keeping up to speed with fast-changing technology, and driving maximum value from existing networks - all while reducing CapEX and OpEX and ensuring Quality of Service (QoS) for the network and Quality of Experience (QoE) for the user. These are just some of the pressing business issues faced by mobileservice providers, summarized by the demand to "achieve more, for less." The ultimate goal of optimization techniques at the network and application layer is to ensure End-user perceived QoS. The next generation networks (NGN), a composite environment of proven telecommunications and Internet-oriented mechanisms have become generally recognized as the telecommunications environment of the future. However, the nature of the NGN environment presents several complex issues regarding quality assurance that have not existed in the legacy environments (e.g., multi-network, multi-vendor, and multi-operator IP-based telecommunications environment, distributed intelligence, third-party provisioning, fixed-wireless and mobile access, etc.). In this Research Paper, a service aware policy-based approach to NGN quality assurance is presented, taking into account both perceptual quality of experience and technologydependant quality of service issues. The respective procedures, entities, mechanisms, and profiles are discussed. The purpose of the presented approach is in research, development, and discussion of pursuing the end-to-end controllability of the quality of the multimedia NGN-based communications in an environment that is best effort in its nature and promotes end user's access agnosticism, service agility, and global mobility.


Design and Implementation VOIP Service on Open IMS and Asterisk Servers Interconnected through Enum Server

Abstract: Asterisk and Open IMS use SIP signal protocol to enable both of them can be connected. To facilitate both relationships, Enum server- that is able to translate the numbering address such as PSTN (E.164) to URI address (Uniform Resource Identifier)- can be used. In this research, we interconnect Open IMS and Asterisk server Enum server. We then analyze the server performance and PDD (Post Dial Delay) values resulted by the system. As the result of the experiment, we found that, for a call from Open IMS user to analog Asterisk telephone (FXS) with a arrival call each servers is 30 call/sec, the maximum PDD value is 493.656 ms. Open IMS is able to serve maximum 30 call/s with computer processor 1.55 GHz, while the Asterisk with computer processor 3.0 GHz, may serve up to 55 call/sec. Enum on server with 1.15 GHz computer processor have the capability of serving maximum of 8156 queries/sec.


Cross Layer Aware Adaptive MAC based on Knowledge Based Reasoning for Cognitive Radio Computer Networks

Abstract: In this paper we are proposing a new concept in MAC layer protocol design for Cognitive radio by combining information held by physical layer and MAC layer with analytical engine based on knowledge based reasoning approach. In the proposed system a cross layer information regarding signal to interference and noise ratio (SINR) and received power are analyzed with help of knowledge based reasoning system to determine minimum power to transmit and size of contention window, to minimize backoff, collision, save power and drop packets. The performance analysis of the proposed protocol indicates improvement in power saving, lowering backoff and significant decrease in number of drop packets. The simulation environment was implement using OMNET++ discrete simulation tool with Mobilty framework and MiXiM simulation library.