Designing and Embedding Reliable Virtual Infrastructures

Abstract: In a virtualized infrastructure where physical resources are shared, a single physical server failure will terminate several virtual servers and crippling the virtual infrastructures which contained those virtual servers. In the worst case, more failures may cascade from overloading the remaining servers. To guarantee some level of reliability, each virtual infrastructure, at instantiation, should be augmented with backup virtual nodes and links that have sufficient capacities. This ensures that, when physical failures occur, sufficient computing resources are available and the virtual network topology is preserved. However, in doing so, the utilization of the physical infrastructure may be greatly reduced. This can be circumvented if backup resources are pooled and shared across multiple virtual infrastructures, and intelligently embedded in the physical infrastructure. These techniques can reduce the physical footprint of virtual backups while guaranteeing reliability.


Algorithmic Aspects of Golomb Ruler Construction

Abstract: We consider Golomb rulers and their construction. Common rulers feature marks at every unit measure, distances can often be measured with numerous pairs of marks. On Golomb rulers, for every distance there are at most two marks measuring it. The construction of optimal---with respect to shortest length for given number of marks or maximum number of marks for given length---is nontrivial, various problems regarding this are NP-complete. We give a simplified hardness proof for one of them. We use a hypergraph characterization of rulers and Golomb rulers to illuminate structural properties. This gives rise to a problem kernel in a fixed-parameter approach to a construction problem. We also take a short look at the practical implications of these considerations.


Simple Wriggling is Hard unless You Are a Fat Hippo

Abstract: We prove that it is NP-hard to decide whether two points in a polygonal domain with holes can be connected by a wire. This implies that finding any approximation to the shortest path for a long snake amidst polygonal obstacles is NP-hard. On the positive side, we show that snake's problem is "length-tractable": if the snake is "fat", i.e., its length/width ratio is small, the shortest path can be computed in polynomial time.


Attribute oriented induction with star schema

Abstract: This paper will propose a novel star schema attribute induction as a new attribute induction paradigm and as improving from current attribute oriented induction. A novel star schema attribute induction will be examined with current attribute oriented induction based on characteristic rule and using non rule based concept hierarchy by implementing both of approaches. In novel star schema attribute induction some improvements have been implemented like elimination threshold number as maximum tuples control for generalization result, there is no ANY as the most general concept, replacement the role concept hierarchy with concept tree, simplification for the generalization strategy steps and elimination attribute oriented induction algorithm. Novel star schema attribute induction is more powerful than the current attribute oriented induction since can produce small number final generalization tuples and there is no ANY in the results.


A Data Warehouse Assistant Design System Based on Clover Model

Abstract: Nowadays, Data Warehouse (DW) plays a crucial role in the process of decision making. However, their design remains a very delicate and difficult task either for expert or users. The goal of this paper is to propose a new approach based on the clover model, destined to assist users to design a DW. The proposed approach is based on two main steps. The first one aims to guide users in their choice of DW schema model. The second one aims to finalize the chosen model by offering to the designer views related to former successful DW design experiences.


Efficient Support Coupled Frequent Pattern Mining Over Progressive Databases

Abstract: There have been many recent studies on sequential pattern mining. The sequential pattern mining on progressive databases is relatively very new, in which we progressively discover the sequential patterns in period of interest. Period of interest is a sliding window continuously advancing as the time goes by. As the focus of sliding window changes, the new items are added to the dataset of interest and obsolete items are removed from it and become up to date. In general, the existing proposals do not fully explore the real world scenario, such as items associated with support in data stream applications such as market basket analysis. Thus mining important knowledge from supported frequent items becomes a non trivial research issue. Our proposed novel approach efficiently mines frequent sequential pattern coupled with support using progressive mining tree.


Dynamic management of transactions in distributed real-time processing system

Abstract: Managing the transactions in real time distributed computing system is not easy, as it has heterogeneously networked computers to solve a single problem. If a transaction runs across some different sites, it may commit at some sites and may failure at another site, leading to an inconsistent transaction. The complexity is increase in real time applications by placing deadlines on the response time of the database system and transactions processing. Such a system needs to process Transactions before these deadlines expired. A series of simulation study have been performed to analyze the performance under different transaction management under conditions such as different workloads, distribution methods, execution mode-distribution and parallel etc. The scheduling of data accesses are done in order to meet their deadlines and to minimize the number of transactions that missed deadlines. A new concept is introduced to manage the transactions in dynamic ways rather than setting computing parameters in static ways. With this approach, the system gives a significant improvement in performance.


Client-to-Client Streaming Scheme for VOD Applications

Abstract: In this paper, we propose an efficient client-to-client streaming approach to cooperatively stream the video using chaining technique with unicast communication among the clients. This approach considers two major issues of VoD 1) Prefix caching scheme to accommodate more number of videos closer to client, so that the request-service delay for the user can be minimized. 2) Cooperative proxy and client chaining scheme for streaming the videos using unicasting. This approach minimizes the client rejection rate and bandwidth requirement on server to proxy and proxy to client path. Our simulation results show that the proposed approach achieves reduced client waiting time and optimal prefix caching of videos minimizing server to proxy path bandwidth usage by utilizing the client to client bandwidth, which is occasionally used when compared to busy server to proxy path bandwidth.


Content Based Image Retrieval Using Exact Legendre Moments and Support Vector Machine

Abstract: Content Based Image Retrieval (CBIR) systems based on shape using invariant image moments, viz., Moment Invariants (MI) and Zernike Moments (ZM) are available in the literature. MI and ZM are good at representing the shape features of an image. However, non-orthogonality of MI and poor reconstruction of ZM restrict their application in CBIR. Therefore, an efficient and orthogonal moment based CBIR system is needed. Legendre Moments (LM) are orthogonal, computationally faster, and can represent image shape features compactly. CBIR system using Exact Legendre Moments (ELM) for gray scale images is proposed in this work. Superiority of the proposed CBIR system is observed over other moment based methods, viz., MI and ZM in terms of retrieval efficiency and retrieval time. Further, the classification efficiency is improved by employing Support Vector Machine (SVM) classifier. Improved retrieval results are obtained over existing CBIR algorithm based on Stacked Euler Vector (SERVE) combined with Modified Moment Invariants (MMI).


Query Routing and Processing in Peer-To-Peer Data Sharing Systems

Abstract: Sharing musical files via the Internet was the essential motivation of early P2P systems. Despite of the great success of the P2P file sharing systems, these systems support only "simple" queries. The focus in such systems is how to carry out an efficient query routing in order to find the nodes storing a desired file. Recently, several research works have been made to extend P2P systems to be able to share data having a fine granularity (i.e. atomic attribute) and to process queries written with a highly expressive language (i.e. SQL). These works have led to the emergence of P2P data sharing systems that represent a new generation of P2P systems and, on the other hand, a next stage in a long period of the database research area. ? The characteristics of P2P systems (e.g. large-scale, node autonomy and instability) make impractical to have a global catalog that represents often an essential component in traditional database systems. Usually, such a catalog stores information about data, schemas and data sources. Query routing and processing are two problems affected by the absence of a global catalog. Locating relevant data sources and generating a close to optimal execution plan become more difficult. In this paper, we concentrate our study on proposed solutions for the both problems. Furthermore, selected case studies of main P2P data sharing systems are analyzed and compared.


Detection of Bleeding in Wireless Capsule Endoscopy Images Using Range Ratio Color

Abstract: Wireless Capsule Endoscopy (WCE) is device to detect abnormalities in colon,esophagus,small intestinal and stomach, to distinguish bleeding in WCE images from non bleeding is a hard job by human reviewing and very time consuming. Consequently, automation for classifying bleeding frames not only will expedite the process but will reduce the burden on the doctors. Using the purity of the red color we can detect the Bleeding areas in WCE images. But, we could find various intensity of red color values in different parts of the small intestinal,so it is not enough to depend on the red color feature alone. We select RGB(Red,Green,Blue) because it takes raw level values and it is easy to use. In this paper we will put range ratio color for each of R,G,and B. Therefore, we divide each image into multiple pixels and apply the range ratio color condition for each pixel. Then we count the number of the pixels that achieved our condition. If the number of pixels grater than zero, then the frame is classified as a bleeding type. Otherwise, it is a non-bleeding. Our experimental results show that this method could achieve a very high accuracy in detecting bleeding images for the different parts of the small intestinal


A Low Overhead Minimum Process Global Snapshop Collection Algorithm for Mobile Distributed System

Abstract: Coordinated checkpointing is an effective fault tolerant technique in distributed system as it avoids the domino effect and require minimum storage requirement. Most of the earlier coordinated checkpoint algorithms block their computation during checkpointing and forces minimum-process or non-blocking but forces all nodes to takes checkpoint even though many of them may not be necessary or non-blocking minimum-process but takes useless checkpoints or reduced useless checkpoint but has higher synchronization message overhead or has high checkpoint request propagation time. Hence in mobile distributed systems there is a great need of minimizing the number of communication message and checkpointing overhead as it raise new issues such as mobility, low bandwidth of wireless channels, frequently disconnections, limited battery power and lack of reliable stable storage on mobile nodes. In this paper, we propose a minimum-process coordinated checkpointing algorithm for mobile distributed system where no useless checkpoints are taken, no blocking of processes takes place and enforces a minimum-number of processes to take checkpoints. Our algorithm imposes low memory and computation overheads on MH's and low communication overheads on wireless channels. It avoids awakening of an MH if it is not required to take its checkpoint and has reduced latency time as each process involved in a global checkpoint can forward its own decision directly to the checkpoint initiator.


Bidimensionality and EPTAS

Abstract: Bidimensionality theory is a powerful framework for the development of metaalgorithmic techniques. It was introduced by Demaine et al. as a tool to obtain sub-exponential time parameterized algorithms for problems on H-minor free graphs. Demaine and Hajiaghayi extended the theory to obtain PTASs for bidimensional problems, and subsequently improved these results to EPTASs. Fomin et. al related the theory to the existence of linear kernels for parameterized problems. In this paper we revisit bidimensionality theory from the perspective of approximation algorithms and redesign the framework for obtaining EPTASs to be more powerful, easier to apply and easier to understand. Two of the most widely used approaches to obtain PTASs on planar graphs are the Lipton-Tarjan separator based approach, and Baker's approach. Demaine and Hajiaghayi strengthened both approaches using bidimensionality and obtained EPTASs for a multitude of problems. We unify the two strenghtened approaches to combine the best of both worlds. At the heart of our framework is a decomposition lemma which states that for "most" bidimensional problems, there is a polynomial time algorithm which given an H-minor-free graph G as input and an e > 0 outputs a vertex set X of size e * OPT such that the treewidth of G n X is f(e). Here, OPT is the objective function value of the problem in question and f is a function depending only on e. This allows us to obtain EPTASs on (apex)-minor-free graphs for all problems covered by the previous framework, as well as for a wide range of packing problems, partial covering problems and problems that are neither closed under taking minors, nor contractions. To the best of our knowledge for many of these problems including cycle packing, vertex-h-packing, maximum leaf spanning tree, and partial r-dominating set no EPTASs on planar graphs were previously known.


On the clustering aspect of nonnegative matrix factorization

Abstract: This paper provides a theoretical explanation on the clustering aspect of nonnegative matrix factorization (NMF). We prove that even without imposing orthogonality nor sparsity constraint on the basis and/or coefficient matrix, NMF still can give clustering results, thus providing a theoretical support for many works, e.g., Xu et al. [1] and Kim et al. [2], that show the superiority of the standard NMF as a clustering method.


Quantitative parametrization of texts written by Ivan Franko: An attempt of the project

Abstract: In the article, the project of quantitative parametrization of all texts by Ivan Franko is manifested. It can be made only by using modern computer techniques after the frequency dictionaries for all Franko's works are compiled. The paper describes the application spheres, methodology, stages, principles and peculiarities in the compilation of the frequency dictionary of the second half of the 19th century - the beginning of the 20th century. The relation between the Ivan Franko frequency dictionary, explanatory dictionary of writer's language and text corpus is discussed.


sTeXIDE: An Integrated Development Environment for sTeX Collections

Abstract: Authoring documents in MKM formats like OMDoc is a very tedious task. After years of working on a semantically annotated corpus of sTeX documents (GenCS), we identified a set of common, time-consuming subtasks, which can be supported in an integrated authoring environment. We have adapted the modular Eclipse IDE into sTeXIDE, an authoring solution for enhancing productivity in contributing to sTeX based corpora. sTeXIDE supports context-aware command completion, module management, semantic macro retrieval, and theory graph navigation.


On the Utility of Directional Information for Repositioning Errant Probes in Central Force Optimization

Abstract: Central Force Optimization is a global search and optimization algorithm that searches a decision space by flying "probes" whose trajectories are deterministically computed using two equations of motion. Because it is possible for a probe to fly outside the domain of feasible solutions, a simple errant probe retrieval method has been used previously that does not include the directional information contained in a probe's acceleration vector. This note investigates the effect of adding directionality to the "repositioning factor" approach. As a general proposition, it appears that doing so does not improve convergence speed or accuracy. In fact, adding directionality to the original errant probe retrieval scheme appears to be highly inadvisable. Nevertheless, there may be alternative probe retrieval schemes that do benefit from directional information, and the results reported here may assist in or encourage their development.


An Algebraic Approach for Computing Equilibria of a Subclass of Finite Normal Form Games

Abstract: A Nash equilibrium has become important solution concept for analyzing the decision making in Game theory. In this paper, we consider the problem of computing Nash equilibria of a subclass of generic finite normal form games. We define "rational payoff irrational equilibria games" to be the games with all rational payoffs and all irrational equilibria. We present a purely algebraic method for computing all Nash equilibria of these games that uses knowledge of Galois groups. Some results, showing properties of the class of games, and an example to show working of the method concludes the paper.


Almost Optimal Unrestricted Fast Johnson-Lindenstrauss Transform

Abstract: The problems of random projections and sparse reconstruction have much in common and individually received much attention. Surprisingly, until now they progressed in parallel and remained mostly separate. Here, we employ new tools from probability in Banach spaces that were successfully used in the context of sparse reconstruction to advance on an open problem in random pojection. In particular, we generalize and use an intricate result by Rudelson and Vershynin for sparse reconstruction which uses Dudley's theorem for bounding Gaussian processes. Our main result states that any set of $N = \exp(\tilde{O}(n))$ real vectors in $n$ dimensional space can be linearly mapped to a space of dimension $k=O(\log N\polylog(n))$, while (1) preserving the pairwise distances among the vectors to within any constant distortion and (2) being able to apply the transformation in time $O(n\log n)$ on each vector. This improves on the best known $N = \exp(\tilde{O}(n^{1/2}))$ achieved by Ailon and Liberty and $N = \exp(\tilde{O}(n^{1/3}))$ by Ailon and Chazelle. The dependence in the distortion constant however is believed to be suboptimal and subject to further investigation. For constant distortion, this settles the open question posed by these authors up to a $\polylog(n)$ factor while considerably simplifying their constructions.


Managing Semantic Loss during Query Reformulation in Peer Data Management Systems

Abstract: In this paper we deal with the notion of semantic loss in Peer Data Management Systems (PDMS) queries. We define such a notion and we give a mechanism that discovers semantic loss in a PDMS network. Next, we propose an algorithm that addresses the problem of restoring such a loss. Further evaluation of our proposed algorithm is an ongoing work


On the Fly Query Entity Decomposition Using Snippets

Abstract: One of the most important issues in Information Retrieval is inferring the intents underlying users' queries. Thus, any tool to enrich or to better contextualized queries can proof extremely valuable. Entity extraction, provided it is done fast, can be one of such tools. Such techniques usually rely on a prior training phase involving large datasets. That training is costly, specially in environments which are increasingly moving towards real time scenarios where latency to retrieve fresh informacion should be minimal. In this paper an `on-the-fly' query decomposition method is proposed. It uses snippets which are mined by means of a na\"ive statistical algorithm. An initial evaluation of such a method is provided, in addition to a discussion on its applicability to different scenarios.


Efficient Local Search Algorithms for Known and New Neighborhoods for the Generalized Traveling Salesman Problem

Abstract: The Generalized Traveling Salesman Problem (GTSP) is a well-known combinatorial optimization problem with a host of applications. It is an extension of the Traveling Salesman Problem (TSP) where the set of cities is partitioned into so-called clusters, and the salesman has to visit every cluster exactly once. While the GTSP is a very important combinatorial optimization problem and is well studied in many aspects, the local search algorithms used in the literature are mostly basic adaptations of simple TSP heuristics. Hence, a thorough and deep research of the neighborhoods and local search algorithms specific to the GTSP is required. We formalize the procedure of adaptation of a TSP neighborhood for the GTSP and classify all other existing and some new GTSP neighborhoods. For every neighborhood, we provide efficient exploration algorithms that are often significantly faster than the ones known from the literature. Finally, we compare different local search implementations empirically.


Provenance Views for Module Privacy

Abstract: Scientific workflow systems increasingly store provenance information about the module executions used to produce a data item, as well as the parameter settings and intermediate data items passed between module executions. However, authors/owners of workflows may wish to keep some of this information confidential. In particular, a module may be proprietary, and users should not be able to infer its behavior by seeing mappings between all data inputs and outputs. The problem we address in this paper is the following: Given a workflow, abstractly modeled by a relation R, a privacy requirement \Gamma and costs associated with data. The owner of the workflow decides which data (attributes) to hide, and provides the user with a view R' which is the projection of R over attributes which have not been hidden. The goal is to minimize the cost of hidden data while guaranteeing that individual modules are \Gamma -private. We call this the "secureview" problem. We formally define the problem, study its complexity, and offer algorithmic solutions.


Modern Quantum Technologies of Information Security

Abstract: In this paper, the systematisation and classification of modern quantum technologies of information security against cyber-terrorist attack are carried out. The characteristic of the basic directions of quantum cryptography from the viewpoint of the quantum technologies used is given. A qualitative analysis of the advantages and disadvantages of concrete quantum protocols is made. The current status of the problem of practical quantum cryptography use in telecommunication networks is considered. In particular, a short review of existing commercial systems of quantum key distribution is given.


Empirical learning aided by weak domain knowledge in the form of feature importance

Abstract: Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowledge while being cost effective. Weak knowledge in the form of feature relative importance (FRI) is presented and explained. Feature relative importance is a real valued approximation of a feature's importance provided by experts. Advantage of using this knowledge is demonstrated by IANN, a modified multilayer neural network algorithm. IANN is a very simple modification of standard neural network algorithm but attains significant performance gains. Experimental results in the field of molecular biology show higher performance over other empirical learning algorithms including standard backpropagation and support vector machines. IANN performance is even comparable to a theory refinement system KBANN that uses stronger domain knowledge. This shows Feature relative importance can improve performance of existing empirical learning algorithms significantly with minimal effort.


Multi-View Active Learning in the Non-Realizable Case

Abstract: The sample complexity of active learning under the realizability assumption has been well-studied. The realizability assumption, however, rarely holds in practice. In this paper, we theoretically characterize the sample complexity of active learning in the non-realizable case under multi-view setting. We prove that, with unbounded Tsybakov noise, the sample complexity of multi-view active learning can be $\widetilde{O}(\log\frac{1}{\epsilon})$, contrasting to single-view setting where the polynomial improvement is the best possible achievement. We also prove that in general multi-view setting the sample complexity of active learning with unbounded Tsybakov noise is $\widetilde{O}(\frac{1}{\epsilon})$, where the order of $1/\epsilon$ is independent of the parameter in Tsybakov noise, contrasting to previous polynomial bounds where the order of $1/\epsilon$ is related to the parameter in Tsybakov noise.


A generic tool to generate a lexicon for NLP from Lexicon-Grammar tables

Abstract: Lexicon-Grammar tables constitute a large-coverage syntactic lexicon but they cannot be directly used in Natural Language Processing (NLP) applications because they sometimes rely on implicit information. In this paper, we introduce LGExtract, a generic tool for generating a syntactic lexicon for NLP from the Lexicon-Grammar tables. It is based on a global table that contains undefined information and on a unique extraction script including all operations to be performed for all tables. We also present an experiment that has been conducted to generate a new lexicon of French verbs and predicative nouns.


Implementation of a Cloud Data Server (CDS) for Providing Secure Service in E-Business

Abstract: Cloud Data Servers is the novel approach for providing secure service to e-business .Millions of users are surfing the Cloud for various purposes, therefore they need highly safe and persistent services. Usually hackers target particular Operating Systems or a Particular Controller. Inspiteof several ongoing researches Conventional Web Servers and its Intrusion Detection System might not be able to detect such attacks. So we implement a Cloud Data Server with Session Controller Architecture using Redundancy and Disconnected Data Access Mechanism. In this paper, we generate the hash code using MD5 algorithm. With the help of which we can circumvent even the attacks, which are undefined by traditional Systems .we implement Cloud Data Sever using Java and Hash Code backup Management using My SQL. Here we Implement AES Algorithm for providing more Security for the hash Code. The CDS using the Virtual Controller controls and monitors the Connections and modifications of the page so as to prevent malicious users from hacking the website. In the proposed approach an activity analyzer takes care of intimating the administrator about possible intrusions and the counter measures required to tackle them. The efficiency ratio of our approach is 98.21% compared with similar approaches.


The DMM bound: multivariate (aggregate) separation bounds

Abstract: In this paper we derive aggregate separation bounds, named after Davenport-Mahler-Mignotte (\dmm), on the isolated roots of polynomial systems, specifically on the minimum distance between any two such roots. The bounds exploit the structure of the system and the height of the sparse (or toric) resultant by means of mixed volume, as well as recent advances on aggregate root bounds for univariate polynomials, and are applicable to arbitrary positive dimensional systems. We improve upon Canny's gap theorem \cite{c-crmp-87} by a factor of $\OO(d^{n-1})$, where $d$ bounds the degree of the polynomials, and $n$ is the number of variables. One application is to the bitsize of the eigenvalues and eigenvectors of an integer matrix, which also yields a new proof that the problem is polynomial. We also compare against recent lower bounds on the absolute value of the root coordinates by Brownawell and Yap \cite{by-issac-2009}, obtained under the hypothesis there is a 0-dimensional projection. Our bounds are in general comparable, but exploit sparseness; they are also tighter when bounding the value of a positive polynomial over the simplex. For this problem, we also improve upon the bounds in \cite{bsr-arxix-2009,jp-arxiv-2009}. Our analysis provides a precise asymptotic upper bound on the number of steps that subdivision-based algorithms perform in order to isolate all real roots of a polynomial system. This leads to the first complexity bound of Milne's algorithm \cite{Miln92} in 2D.


An Automated Algorithm for Approximation of Temporal Video Data Using Linear B'EZIER Fitting

Abstract: This paper presents an efficient method for approximation of temporal video data using linear Bezier fitting. For a given sequence of frames, the proposed method estimates the intensity variations of each pixel in temporal dimension using linear Bezier fitting in Euclidean space. Fitting of each segment ensures upper bound of specified mean squared error. Break and fit criteria is employed to minimize the number of segments required to fit the data. The proposed method is well suitable for lossy compression of temporal video data and automates the fitting process of each pixel. Experimental results show that the proposed method yields good results both in terms of objective and subjective quality measurement parameters without causing any blocking artifacts.


Construction et maintien d'une for\^et couvrante dans un r\'eseau dynamique

Abstract: In this work we introduce the principles of an algorithm that constructs and maintains a spanning forest in a mobile telecommunication network-a MANET. The algorithm is based on the random walk of a token and is entirely decentralized. A probability analysis is performed when the network is static. Then we show that performances can be slightly enhanced when adding a memory process in the walk on the token.


A Tree Logic with Graded Paths and Nominals

Abstract: Regular tree grammars and regular path expressions constitute core constructs widely used in programming languages and type systems. Nevertheless, there has been little research so far on reasoning frameworks for path expressions where node cardinality constraints occur along a path in a tree. We present a logic capable of expressing deep counting along paths which may include arbitrary recursive forward and backward navigation. The counting extensions can be seen as a generalization of graded modalities that count immediate successor nodes. While the combination of graded modalities, nominals, and inverse modalities yields undecidable logics over graphs, we show that these features can be combined in a tree logic decidable in exponential time.


Distributed Creation and Adaptation of Random Scale-Free Overlay Networks

Abstract: Random scale-free overlay topologies provide a number of properties like for example high resilience against failures of random nodes, small (average) diameter as well as good expansion and congestion characteristics that make them interesting for the use in large-scale distributed systems. A number of these properties have been shown to be influenced by the exponent \gamma of their degree distribution P(k) ~ k^{-\gamma}. In this article, we present a distributed rewiring scheme that is suitable to effectuate scale-free overlay topologies with an adjustable exponent. The scheme uses a biased random walk strategy to sample new endpoints of edges being rewired and relies on a simple equilibrium model for scale-free networks. The bias of the random walk strategy can be tuned to produce random scale-free networks with arbitrary degree distribution exponents greater than two. We argue that the rewiring strategy can be implemented in a distributed fashion based on a node's information about its immediate neighbors. We present both analytical arguments as well as results that have been obtained using an implementation of the proposed protocol.


Reliable Self-Stabilizing Communication for Quasi Rendezvous

Abstract: The paper presents three self-stabilizing protocols for basic fair and reliable link communication primitives. We assume a link-register communication model under read/write atomicity, where every process can read from but cannot write into its neighbours' registers. The first primitive guarantees that any process writes a new value in its register(s) only after all its neighbours have read the previous value, whatever the initial scheduling of processes' actions. The second primitive implements a "weak rendezvous" communication mechanism by using an alternating bit protocol: whenever a process consecutively writes n values (possibly the same ones) in a register, each neighbour is guaranteed to read each value from the register at least once. On the basis of the previous protocol, the third primitive implements a "quasi rendezvous": in words, this primitive ensures furthermore that there exists exactly one reading between two writing operations All protocols are self-stabilizing and run in asynchronous arbitrary networks. The goal of the paper is in handling each primitive by a separate procedure, which can be used as a "black box" in more involved self-stabilizing protocols.


Experimental Comparisons of Derivative Free Optimization Algorithms

Abstract: In this paper, the performances of the quasi-Newton BFGS algorithm, the NEWUOA derivative free optimizer, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the Differential Evolution (DE) algorithm and Particle Swarm Optimizers (PSO) are compared experimentally on benchmark functions reflecting important challenges encountered in real-world optimization problems. Dependence of the performances in the conditioning of the problem and rotational invariance of the algorithms are in particular investigated.


Transforming Outermost into Context-Sensitive Rewriting

Abstract: We define two transformations from term rewriting systems (TRSs) to context-sensitive TRSs in such a way that termination of the target system implies outermost termination of the original system. In the transformation based on 'context extension', each outermost rewrite step is modeled by exactly one step in the transformed system. This transformation turns out to be complete for the class of left-linear TRSs. The second transformation is called `dynamic labeling' and results in smaller sized context-sensitive TRSs. Here each modeled step is adjoined with a small number of auxiliary steps. As a result state-of-the-art termination methods for context-sensitive rewriting become available for proving termination of outermost rewriting. Both transformations have been implemented in Jambox, making it the most successful tool in the category of outermost rewriting of the last edition of the annual termination competition.


On the contribution of backward jumps to instruction sequence expressiveness

Abstract: We investigate the expressiveness of backward jumps in a framework of formalized sequential programming called program algebra. We show that - if expressiveness is measured in terms of the computability of partial Boolean functions - then backward jumps are superfluous. If we, however, want to prevent explosion of the length of programs, then backward jumps are essential.


A Study of Geolocation Databases

Abstract: The geographical location of Internet IP addresses has an importance both for academic research and commercial applications. Thus, both commercial and academic databases and tools are available for mapping IP addresses to geographic locations. Evaluating the accuracy of these mapping services is complex since obtaining diverse large scale ground truth is very hard. In this work we evaluate mapping services using an algorithm that groups IP addresses to PoPs, based on structure and delay. This way we are able to group close to 100,000 IP addresses world wide into groups that are known to share a geo-location with high confidence. We provide insight into the strength and weaknesses of IP geolocation databases, and discuss their accuracy and encountered anomalies.


Normalized Range Voting Broadly Resists Control

Abstract: We study the behavior of Range Voting and Normalized Range Voting with respect to electoral control. Electoral control encompasses attempts from an election chair to alter the structure of an election in order to change the outcome. We show that a voting system resists a case of control by proving that performing that case of control is computationally infeasible. Range Voting is a natural extension of approval voting, and Normalized Range Voting is a simple variant which alters each vote to maximize the potential impact of each voter. We show that Normalized Range Voting has among the largest number of control resistances among natural voting systems.


SM stability for time-dependent problems

Abstract: Various classes of stable finite difference schemes can be constructed to obtain a numerical solution. It is important to select among all stable schemes such a scheme that is optimal in terms of certain additional criteria. In this study, we use a simple boundary value problem for a one-dimensional parabolic equation to discuss the selection of an approximation with respect to time. We consider the pure diffusion equation, the pure convective transport equation and combined convection-diffusion phenomena. Requirements for the unconditionally stable finite difference schemes are formulated that are related to retaining the main features of the differential problem. The concept of SM stable finite difference scheme is introduced. The starting point are difference schemes constructed on the basis of the various Pad$\acute{e}$ approximations.


A New Framework for Join Product Skew

Abstract: Different types of data skew can result in load imbalance in the context of parallel joins under the shared nothing architecture. We study one important type of skew, join product skew (JPS). A static approach based on frequency classes is proposed which takes for granted the data distribution of join attribute values. It comes from the observation that the join selectivity can be expressed as a sum of products of frequencies of the join attribute values. As a consequence, an appropriate assignment of join sub-tasks, that takes into consideration the magnitude of the frequency products can alleviate the join product skew. Motivated by the aforementioned remark, we propose an algorithm, called Handling Join Product Skew (HJPS), to handle join product skew.


An Implicit Characterization of PSPACE

Abstract: We present a type system for an extension of lambda calculus with a conditional construction, named STAB, that characterizes the PSPACE class. This system is obtained by extending STA, a type assignment for lambda-calculus inspired by Lafont's Soft Linear Logic and characterizing the PTIME class. We extend STA by means of a ground type and terms for booleans and conditional. The key issue in the design of the type system is to manage the contexts in the rule for conditional in an additive way. Thanks to this rule, we are able to program polynomial time Alternating Turing Machines. From the well-known result APTIME = PSPACE, it follows that STAB is complete for PSPACE. Conversely, inspired by the simulation of Alternating Turing machines by means of Deterministic Turing machine, we introduce a call-by-name evaluation machine with two memory devices in order to evaluate programs in polynomial space. As far as we know, this is the first characterization of PSPACE that is based on lambda calculus and light logics.


Ivan Franko's novel Dlja domashnjoho ohnyshcha (For the Hearth) in the light of the frequency dictionary

Abstract: In the article, the methodology and the principles of the compilation of the Frequency dictionary for Ivan Franko's novel Dlja domashnjoho ohnyshcha (For the Hearth) are described. The following statistical parameters of the novel vocabulary are obtained: variety, exclusiveness, concentration indexes, correlation between word rank and text coverage, etc. The main quantitative characteristics of Franko's novels Perekhresni stezhky (The Cross-Paths) and Dlja domashnjoho ohnyshcha are compared on the basis of their frequency dictionaries.


Perfusion Linearity and Its Applications

Abstract: Perfusion analysis computes blood flow parameters (blood volume, blood flow, mean transit time) from the observed flow of contrast agent, passing through the patient's vascular system. Perfusion deconvolution has been widely accepted as the principal numerical tool for perfusion analysis, and is used routinely in clinical applications. This extensive use of perfusion in clinical decision-making makes numerical stability and robustness of perfusion computations vital for accurate diagnostics and patient safety. The main goal of this paper is to propose a novel approach for validating numerical properties of perfusion algorithms. The approach is based on Perfusion Linearity Property (PLP), which we find in perfusion deconvolution, as well as in many other perfusion techniques. PLP allows one to study perfusion values as weighted averages of the original imaging data. This, in turn, uncovers hidden problems with the existing deconvolution techniques, and may be used to suggest more reliable computational approaches and methodology.


Balancing congestion for unsplittable routing on a bidirected ring

Abstract: Given a bidirected ring with capacities and a demand graph, we present an approximation algorithm to the problem of finding the minimum $\alpha$ such that there exists a feasible unsplittable routing of the demands after multiplying each capacity by $\alpha$. We also give an approximation scheme to the problem.


The Complexity of Reasoning for Fragments of Autoepistemic Logic

Abstract: Autoepistemic logic extends propositional logic by the modal operator L. A formula that is preceded by an L is said to be "believed". The logic was introduced by Moore 1985 for modeling an ideally rational agent's behavior and reasoning about his own beliefs. In this paper we analyze all Boolean fragments of autoepistemic logic with respect to the computational complexity of the three most common decision problems expansion existence, brave reasoning and cautious reasoning. As a second contribution we classify the computational complexity of counting the number of stable expansions of a given knowledge base. To the best of our knowledge this is the first paper analyzing the counting problem for autoepistemic logic.


Performance of a Concurrent Link SDMA MAC under Practical PHY Operating Conditions

Abstract: Space Division Multiple Access (SDMA) based Medium Access Control (MAC) protocols have been proposed to enable concurrent communications and improve link throughput in Multi-Input Multi-Output (MIMO) Ad Hoc networks. For the most part, the works appearing in the literature make idealized and simplifying assumptions about the underlying physical layer as well as some aspects of the link adaptation protocol. The result is that the performance predicted by such works may not necessarily be a good predictor of actual performance in a fully deployed system. In this paper we look to introduce elements into the SDMA MAC concept that would allow us to better predict their performance under realistic operating conditions. Using a generic SDMA-MAC we look at how the network sum throughput changes with the introduction of the following: $(a)$ use of the more practical MMSE algorithm instead of the zero-forcing or SVD based nulling algorithms used for receive beamnulling; $(b)$ impact of channel estimation errors; $(c)$ introduction of link adaptation mechanism specifically designed for concurrent SDMA MACs; $(d)$ incorporation of TX beamforming along with RX beamnulling. Following on the transmission window during which concurrent transmissions are allowed by the MAC, we qualify the impact of each of these four elements in isolation. At the conclusion, the performance of a system that incorporates elements $a-d$ is presented and compared against the baseline system, showing an improvement of up to 5x in the overall network sum throughput.


Stream Control Transmission Protocol Steganography

Abstract: Stream Control Transmission Protocol (SCTP) is a new transport layer protocol that is due to replace TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) protocols in future IP networks. Currently, it is implemented in such operating systems like BSD, Linux, HP-UX or Sun Solaris. It is also supported in Cisco network devices operating system (Cisco IOS) and may be used in Windows. This paper describes potential steganographic methods that may be applied to SCTP and may pose a threat to network security. Proposed methods utilize new, characteristic SCTP features like multi-homing and multistreaming. Identified new threats and suggested countermeasures may be used as a supplement to RFC 5062, which describes security attacks in SCTP protocol and can induce further standard modifications.


Learning Probabilistic Hierarchical Task Networks to Capture User Preferences

Abstract: We propose automatically learning probabilistic Hierarchical Task Networks (pHTNs) in order to capture a user's preferences on plans, by observing only the user's behavior. HTNs are a common choice of representation for a variety of purposes in planning, including work on learning in planning. Our contributions are (a) learning structure and (b) representing preferences. In contrast, prior work employing HTNs considers learning method preconditions (instead of structure) and representing domain physics or search control knowledge (rather than preferences). Initially we will assume that the observed distribution of plans is an accurate representation of user preference, and then generalize to the situation where feasibility constraints frequently prevent the execution of preferred plans. In order to learn a distribution on plans we adapt an Expectation-Maximization (EM) technique from the discipline of (probabilistic) grammar induction, taking the perspective of task reductions as productions in a context-free grammar over primitive actions. To account for the difference between the distributions of possible and preferred plans we subsequently modify this core EM technique, in short, by rescaling its input.


M\'{e}todos para la Selecci\'{o}n y el Ajuste de Caracter\'{i}sticas en el Problema de la Detecci\'{o}n de Spam

Abstract: The email is used daily by millions of people to communicate around the globe and it is a mission-critical application for many businesses. Over the last decade, unsolicited bulk email has become a major problem for email users. An overwhelming amount of spam is flowing into users' mailboxes daily. In 2004, an estimated 62% of all email was attributed to spam. Spam is not only frustrating for most email users, it strains the IT infrastructure of organizations and costs businesses billions of dollars in lost productivity. In recent years, spam has evolved from an annoyance into a serious security threat, and is now a prime medium for phishing of sensitive information, as well the spread of malicious software. This work presents a first approach to attack the spam problem. We propose an algorithm that will improve a classifier's results by adjusting its training set data. It improves the document's vocabulary representation by detecting good topic descriptors and discriminators.


The dilation of the Delaunay triangulation is greater than {\pi}/2

Abstract: Consider the Delaunay triangulation T of a set P of points in the plane as a Euclidean graph, in which the weight of every edge is its length. It has long been conjectured that the dilation in T of any pair p, p \in P, which is the ratio of the length of the shortest path from p to p' in T over the Euclidean distance ||pp'||, can be at most {\pi}/2 \approx 1.5708. In this paper, we show how to construct point sets in convex position with dilation > 1.5810 and in general position with dilation > 1.5846. Furthermore, we show that a sufficiently large set of points drawn independently from any distribution will in the limit approach the worst-case dilation for that distribution.


Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges

Abstract: Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.


Brain-Like Stochastic Search: A Research Challenge and Funding Opportunity

Abstract: Brain-Like Stochastic Search (BLiSS) refers to this task: given a family of utility functions U(u,A), where u is a vector of parameters or task descriptors, maximize or minimize U with respect to u, using networks (Option Nets) which input A and learn to generate good options u stochastically. This paper discusses why this is crucial to brain-like intelligence (an area funded by NSF) and to many applications, and discusses various possibilities for network design and training. The appendix discusses recent research, relations to work on stochastic optimization in operations research, and relations to engineering-based approaches to understanding neocortex.


Computing the speed of convergence of ergodic averages and pseudorandom points in computable dynamical systems

Abstract: A pseudorandom point in an ergodic dynamical system over a computable metric space is a point which is computable but its dynamics has the same statistical behavior as a typical point of the system. It was proved in [Avigad et al. 2010, Local stability of ergodic averages] that in a system whose dynamics is computable the ergodic averages of computable observables converge effectively. We give an alternative, simpler proof of this result. This implies that if also the invariant measure is computable then the pseudorandom points are a set which is dense (hence nonempty) on the support of the invariant measure.


On the Weak Computability of Continuous Real Functions

Abstract: In computable analysis, sequences of rational numbers which effectively converge to a real number x are used as the (rho-) names of x. A real number x is computable if it has a computable name, and a real function f is computable if there is a Turing machine M which computes f in the sense that, M accepts any rho-name of x as input and outputs a rho-name of f(x) for any x in the domain of f. By weakening the effectiveness requirement of the convergence and classifying the converging speeds of rational sequences, several interesting classes of real numbers of weak computability have been introduced in literature, e.g., in addition to the class of computable real numbers (EC), we have the classes of semi-computable (SC), weakly computable (WC), divergence bounded computable (DBC) and computably approximable real numbers (CA). In this paper, we are interested in the weak computability of continuous real functions and try to introduce an analogous classification of weakly computable real functions. We present definitions of these functions by Turing machines as well as by sequences of rational polygons and prove these two definitions are not equivalent. Furthermore, we explore the properties of these functions, and among others, show their closure properties under arithmetic operations and composition.


Computation with Advice

Abstract: Computation with advice is suggested as generalization of both computation with discrete advice and Type-2 Nondeterminism. Several embodiments of the generic concept are discussed, and the close connection to Weihrauch reducibility is pointed out. As a novel concept, computability with random advice is studied; which corresponds to correct solutions being guessable with positive probability. In the framework of computation with advice, it is possible to define computational complexity for certain concepts of hypercomputation. Finally, some examples are given which illuminate the interplay of uniform and non-uniform techniques in order to investigate both computability with advice and the Weihrauch lattice.


The Cardinality of an Oracle in Blum-Shub-Smale Computation

Abstract: We examine the relation of BSS-reducibility on subsets of the real numbers. The question was asked recently (and anonymously) whether it is possible for the halting problem H in BSS-computation to be BSS-reducible to a countable set. Intuitively, it seems that a countable set ought not to contain enough information to decide membership in a reasonably complex (uncountable) set such as H. We confirm this intuition, and prove a more general theorem linking the cardinality of the oracle set to the cardinality, in a local sense, of the set which it computes. We also mention other recent results on BSS-computation and algebraic real numbers.


The descriptive set-theoretic complexity of the set of points of continuity of a multi-valued function (Extended Abstract)

Abstract: In this article we treat a notion of continuity for a multi-valued function F and we compute the descriptive set-theoretic complexity of the set of all x for which F is continuous at x. We give conditions under which the latter set is either a G_\delta set or the countable union of G_\delta sets. Also we provide a counterexample which shows that the latter result is optimum under the same conditions. Moreover we prove that those conditions are necessary in order to obtain that the set of points of continuity of F is Borel i.e., we show that if we drop some of the previous conditions then there is a multi-valued function F whose graph is a Borel set and the set of points of continuity of F is not a Borel set. Finally we give some analogue results regarding a stronger notion of continuity for a multi-valued function. This article is motivated by a question of M. Ziegler in "Real Computation with Least Discrete Advice: A Complexity Theory of Nonuniform Computability with Applications to Linear Algebra", (submitted).


Computing the Solutions of the Combined Korteweg-de Vries Equation by Turing Machines

Abstract: In this paper, we study the computability of the initial value problem of the Combined KdV equation. It is shown that, for any integer s>2, the nonlinear solution operator which maps an initial condition data to the solution of the Combined KdV equation can be computed by a Turing machine.


Making big steps in trajectories

Abstract: We consider the solution of initial value problems within the context of hybrid systems and emphasise the use of high precision approximations (in software for exact real arithmetic). We propose a novel algorithm for the computation of trajectories up to the area where discontinuous jumps appear, applicable for holomorphic flow functions. Examples with a prototypical implementation illustrate that the algorithm might provide results with higher precision than well-known ODE solvers at a similar computation time.


A Local to Global Principle for the Complexity of Riemann Mappings (Extended Abstract)

Abstract: We show that the computational complexity of Riemann mappings can be bounded by the complexity needed to compute conformal mappings locally at boundary points. As a consequence we get first formally proven upper bounds for Schwarz-Christoffel mappings and, more generally, Riemann mappings of domains with piecewise analytic boundaries.


NP-Logic Systems and Model-Equivalence Reductions

Abstract: In this paper we investigate the existence of model-equivalence reduction between NP-logic systems which are logic systems with model existence problem in NP. It is shown that among all NP-systems with model checking problem in NP, the existentially quantified propositional logic (\exists PF) is maximal with respect to poly-time model-equivalent reduction. However, \exists PF seems not a maximal NP-system in general because there exits a NP-system with model checking problem D^P-complete.


Computational Complexity of Iterated Maps on the Interval (Extended Abstract)

Abstract: The exact computation of orbits of discrete dynamical systems on the interval is considered. Therefore, a multiple-precision floating point approach based on error analysis is chosen and a general algorithm is presented. The correctness of the algorithm is shown and the computational complexity is analyzed. As a main result, the computational complexity measure considered here is related to the Ljapunow exponent of the dynamical system under consideration.


A Rigorous Extension of the Sch\"onhage-Strassen Integer Multiplication Algorithm Using Complex Interval Arithmetic

Abstract: Multiplication of n-digit integers by long multiplication requires O(n^2) operations and can be time-consuming. In 1970 A. Schoenhage and V. Strassen published an algorithm capable of performing the task with only O(n log(n)) arithmetic operations over the complex field C; naturally, finite-precision approximations to C are used and rounding errors need to be accounted for. Overall, using variable-precision fixed-point numbers, this results in an O(n(log(n))^(2+Epsilon))-time algorithm. However, to make this algorithm more efficient and practical we need to make use of hardware-based floating-point numbers. How do we deal with rounding errors? and how do we determine the limits of the fixed-precision hardware? Our solution is to use interval arithmetic to guarantee the correctness of results and determine the hardware's limits. We examine the feasibility of this approach and are able to report that 75,000-digit base-256 integers can be handled using double-precision containment sets. This clearly demonstrates that our approach has practical potential; however, at this stage, our implementation does not yet compete with commercial ones, but we are able to demonstrate the feasibility of this technique.


Complete Multi-Representations of Sets in a Computable Measure Space

Abstract: In a recent paper, two multi-representations for the measurable sets in a computable measure space have been introduced, which prove to be topologically complete w.r.t. certain topological properties. In this contribution, we show them recursively complete w.r.t. computability of measure and set-theoretical operations.


A Note on Element-wise Matrix Sparsification via a Matrix-valued Bernstein Inequality

Abstract: Given an n x n matrix A, we present a simple, element-wise sparsification algorithm that zeroes out all sufficiently small elements of A and then retains some of the remaining elements with probabilities proportional to the square of their magnitudes. We analyze the approximation accuracy of the proposed algorithm using a recent, elegant non-commutative Bernstein inequality, and compare our bounds with all existing (to the best of our knowledge) element-wise matrix sparsification algorithms.


Controlled non uniform random generation of decomposable structures

Abstract: Consider a class of decomposable combinatorial structures, using different types of atoms $\Atoms = \{\At_1,\ldots ,\At_{|{\Atoms}|}\}$. We address the random generation of such structures with respect to a size $n$ and a targeted distribution in $k$ of its \emph{distinguished} atoms. We consider two variations on this problem. In the first alternative, the targeted distribution is given by $k$ real numbers $\TargFreq_1, \ldots, \TargFreq_k$ such that $0 < \TargFreq_i < 1$ for all $i$ and $\TargFreq_1+\cdots+\TargFreq_k \leq 1$. We aim to generate random structures among the whole set of structures of a given size $n$, in such a way that the {\em expected} frequency of any distinguished atom $\At_i$ equals $\TargFreq_i$. We address this problem by weighting the atoms with a $k$-tuple $\Weights$ of real-valued weights, inducing a weighted distribution over the set of structures of size $n$. We first adapt the classical recursive random generation scheme into an algorithm taking $\bigO{n^{1+o(1)}+mn\log{n}}$ arithmetic operations to draw $m$ structures from the $\Weights$-weighted distribution. Secondly, we address the analytical computation of weights such that the targeted frequencies are achieved asymptotically, i. e. for large values of $n$. We derive systems of functional equations whose resolution gives an explicit relationship between $\Weights$ and $\TargFreq_1, \ldots, \TargFreq_k$. Lastly, we give an algorithm in $\bigO{k n^4}$ for the inverse problem, {\it i.e.} computing the frequencies associated with a given $k$-tuple $\Weights$ of weights, and an optimized version in $\bigO{k n^2}$ in the case of context-free languages. This allows for a heuristic resolution of the weights/frequencies relationship suitable for complex specifications. In the second alternative, the targeted distribution is given by a $k$ natural numbers $n_1, \ldots, n_k$ such that $n_1+\cdots+n_k+r=n$ where $r \geq 0$ is the number of undistinguished atoms. The structures must be generated uniformly among the set of structures of size $n$ that contain {\em exactly} $n_i$ atoms $\At_i$ ($1 \leq i \leq k$). We give a $\bigO{r^2\prod_{i=1}^k n_i^2 +m n k \log n}$ algorithm for generating $m$ structures, which simplifies into a $\bigO{r\prod_{i=1}^k n_i +m n}$ for regular specifications.


Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields

Abstract: We introduce a new neural architecture and an unsupervised algorithm for learning invariant representations from temporal sequence of images. The system uses two groups of complex cells whose outputs are combined multiplicatively: one that represents the content of the image, constrained to be constant over several consecutive frames, and one that represents the precise location of features, which is allowed to vary over time but constrained to be sparse. The architecture uses an encoder to extract features, and a decoder to reconstruct the input from the features. The method was applied to patches extracted from consecutive movie frames and produces orientation and frequency selective units analogous to the complex cells in V1. An extension of the method is proposed to train a network composed of units with local receptive field spread over a large image of arbitrary size. A layer of complex cells, subject to sparsity constraints, pool feature units over overlapping local neighborhoods, which causes the feature units to organize themselves into pinwheel patterns of orientation-selective receptive fields, similar to those observed in the mammalian visual cortex. A feed-forward encoder efficiently computes the feature representation of full images.


Prediction with Advice of Unknown Number of Experts

Abstract: In the framework of prediction with expert advice, we consider a recently introduced kind of regret bounds: the bounds that depend on the effective instead of nominal number of experts. In contrast to the NormalHedge bound, which mainly depends on the effective number of experts and also weakly depends on the nominal one, we obtain a bound that does not contain the nominal number of experts at all. We use the defensive forecasting method and introduce an application of defensive forecasting to multivalued supermartingales.


Hiding Data in OFDM Symbols of IEEE 802.11 Networks

Abstract: This paper presents a new steganographic method called WiPad (Wireless Padding). It is based on the insertion of hidden data into the padding of frames at the physical layer of WLANs (Wireless Local Area Networks). A performance analysis based on a Markov model, previously introduced and validated by the authors in [10], is provided for the method in relation to the IEEE 802.11 a/g standards. Its results prove that maximum steganographic bandwidth for WiPad is as high as 1.1 Mbit/s for data frames and 0.44 Mbit/s for acknowledgment (ACK) frames. To the authors' best knowledge this is the most capacious of all the known steganographic network channels.


Proceedings Seventh International Conference on Computability and Complexity in Analysis

Abstract: This volume of the Electronic Proceedings in Theoretical Computer Science (EPTCS) contains extended abstracts of talks to be presented at the Seventh International Conference on Computability and Complexity in Analysis (CCA 2010) that will take place in Zhenjiang, China, June 21-25, 2010. This conference is the seventeenth event in the series of CCA annual meetings. The CCA conferences are aimed at promoting the study and advancement of the theory of computability and complexity over real-valued data and its application.


XQ2P: Efficient XQuery P2P Time Series Processing

Abstract: In this demonstration, we propose a model for the management of XML time series (TS), using the new XQuery 1.1 window operator. We argue that centralized computation is slow, and demonstrate XQ2P, our prototype of efficient XQuery P2P TS computation in the context of financial analysis of large data sets (>1M values).


Gestion efficace de s\'eries temporelles en P2P: Application \`a l'analyse technique et l'\'etude des objets mobiles

Abstract: In this paper, we propose a simple generic model to manage time series. A time series is composed of a calendar with a typed value for each calendar entry. Although the model could support any kind of XML typed values, in this paper we focus on real numbers, which are the usual application. We define basic vector space operations (plus, minus, scale), and also relational-like and application oriented operators to manage time series. We show the interest of this generic model on two applications: (i) a stock investment helper; (ii) an ecological transport management system. Stock investment requires window-based operations while trip management requires complex queries. The model has been implemented and tested in PHP, Java, and XQuery. We show benchmark results illustrating that the computing of 5000 series of over 100.000 entries in length - common requirements for both applications - is difficult on classical centralized PCs. In order to serve a community of users sharing time series, we propose a P2P implementation of time series by dividing them in segments and providing optimized algorithms for operator expression computation.


Randomness for Free

Abstract: We consider two-player zero-sum games on graphs. These games can be classified on the basis of the information of the players and on the mode of interaction between them. On the basis of information the classification is as follows: (a) partial-observation (both players have partial view of the game); (b) one-sided complete-observation (one player has complete observation); and (c) complete-observation (both players have complete view of the game). On the basis of mode of interaction we have the following classification: (a) concurrent (both players interact simultaneously); and (b) turn-based (both players interact in turn). The two sources of randomness in these games are randomness in transition function and randomness in strategies. In general, randomized strategies are more powerful than deterministic strategies, and randomness in transitions gives more general classes of games. In this work we present a complete characterization for the classes of games where randomness is not helpful in: (a) the transition function probabilistic transition can be simulated by deterministic transition); and (b) strategies (pure strategies are as powerful as randomized strategies). As consequence of our characterization we obtain new undecidability results for these games.


Impossibility of independence amplification in Kolmogorov complexity theory

Abstract: The paper studies randomness extraction from sources with bounded independence and the issue of independence amplification of sources, using the framework of Kolmogorov complexity. The dependency of strings $x$ and $y$ is ${\rm dep}(x,y) = \max\{C(x) - C(x \mid y), C(y) - C(y\mid x)\}$, where $C(\cdot)$ denotes the Kolmogorov complexity. It is shown that there exists a computable Kolmogorov extractor $f$ such that, for any two $n$-bit strings with complexity $s(n)$ and dependency $\alpha(n)$, it outputs a string of length $s(n)$ with complexity $s(n)- \alpha(n)$ conditioned by any one of the input strings. It is proven that the above are the optimal parameters a Kolmogorov extractor can achieve. It is shown that independence amplification cannot be effectively realized. Specifically, if (after excluding a trivial case) there exist computable functions $f_1$ and $f_2$ such that ${\rm dep}(f_1(x,y), f_2(x,y)) \leq \beta(n)$ for all $n$-bit strings $x$ and $y$ with ${\rm dep}(x,y) \leq \alpha(n)$, then $\beta(n) \geq \alpha(n) - O(\log n)$.


Termination of Rewriting with Right-Flat Rules Modulo Permutative Theories

Abstract: We present decidability results for termination of classes of term rewriting systems modulo permutative theories. Termination and innermost termination modulo permutative theories are shown to be decidable for term rewrite systems (TRS) whose right-hand side terms are restricted to be shallow (variables occur at depth at most one) and linear (each variable occurs at most once). Innermost termination modulo permutative theories is also shown to be decidable for shallow TRS. We first show that a shallow TRS can be transformed into a flat (only variables and constants occur at depth one) TRS while preserving termination and innermost termination. The decidability results are then proved by showing that (a) for right-flat right-linear (flat) TRS, non-termination (respectively, innermost non-termination) implies non-termination starting from flat terms, and (b) for right-flat TRS, the existence of non-terminating derivations starting from a given term is decidable. On the negative side, we show PSPACE-hardness of termination and innermost termination for shallow right-linear TRS, and undecidability of termination for flat TRS.


Secure Neighbor Position Discovery in VANETs

Abstract: Many significant functionalities of vehicular ad hoc networks (VANETs) require that nodes have knowledge of the positions of other vehicles, and notably of those within communication range. However, adversarial nodes could provide false position information or disrupt the acquisition of such information. Thus, in VANETs, the discovery of neighbor positions should be performed in a secure manner. In spite of a multitude of security protocols in the literature, there is no secure discovery protocol for neighbors positions. We address this problem in our paper: we design a distributed protocol that relies solely on information exchange among one-hop neighbors, we analyze its security properties in presence of one or multiple (independent or colluding) adversaries, and we evaluate its performance in a VANET environment using realistic mobility traces. We show that our protocol can be highly effective in detecting falsified position information, while maintaining a low rate of false positive detections.


Tight and simple Web graph compression

Abstract: Analysing Web graphs has applications in determining page ranks, fighting Web spam, detecting communities and mirror sites, and more. This study is however hampered by the necessity of storing a major part of huge graphs in the external memory, which prevents efficient random access to edge (hyperlink) lists. A number of algorithms involving compression techniques have thus been presented, to represent Web graphs succinctly but also providing random access. Those techniques are usually based on differential encodings of the adjacency lists, finding repeating nodes or node regions in the successive lists, more general grammar-based transformations or 2-dimensional representations of the binary matrix of the graph. In this paper we present two Web graph compression algorithms. The first can be seen as engineering of the Boldi and Vigna (2004) method. We extend the notion of similarity between link lists, and use a more compact encoding of residuals. The algorithm works on blocks of varying size (in the number of input lines) and sacrifices access time for better compression ratio, achieving more succinct graph representation than other algorithms reported in the literature. The second algorithm works on blocks of the same size, in the number of input lines, and its key mechanism is merging the block into a single ordered list. This method achieves much more attractive space-time tradeoffs.


On the definition of a theoretical concept of an operating system

Abstract: We dwell on how a definition of a theoretical concept of an operating system, suitable to be incorporated in a mathematical theory of operating systems, could look like. This is considered a valuable preparation for the development of a mathematical theory of operating systems.


Treatment the Effects of Studio Wall Resonance and Coincidence Phenomena for Recording Noisy Speech Via FPGA Digital Filter

Abstract: This work introduces an economic solution for the problems of sound insulation of recording studios. Sound insulation at wall resonance frequency is weak. Instead of acoustical treatment, a digital filter is used to eliminate the effects of wall resonance and coincidence phenomena on recording of speech. Sound insulation of studio is measured to calculate the wall resonance frequency and the coincidence frequency. Pole /zero placement technique is used to calculate the IIR filter coefficients. The digital filter is designed, simulated and implemented. The proposed system is used to treat these problems and it is shown to be effective in recording the noisy speech. In this work digital signal processing is used instead of the acoustic treatment to eliminate the effect of noise at the studio wall resonance. This technique is cheap and effective in canceling the noise at the desired frequencies. Field Programmable Gate Array (FPGA) is used for hardware implementation of the proposed filter structure which provides fast and cheap solution for processing real time audio signals. The implementation is carried out using Spartan chip from Xinlinx achieving higher performance than commercially available software solutions.


Performance of RCPC-Encoded V-BLAST MIMO In Nakagami-m Fading Channel

Abstract: Multiple Input Multiple Output (MIMO) wireless communication link has been theoretically proven to be reliable and capable of achieving high capacity. However, these two advantageous characteristics tend to be addressed separately in many major researches. Researches on various approaches to attain both characteristics in a single MIMO system are still on-going and an established approach is yet to be concluded. To address this problem, in this paper a Vertical Bell Laboratories Layered Space-Time (V-BLAST) MIMO enhanced with Rate-Compatible Convolutional (RCPC) codes with Zero Forcing (ZF) and Minimum Mean Squared Error (MMSE)-based detection is proposed. The analytical BER of the system is presented and numerically analyzed. The system performance is analyzed in Nakagami-m fading channel, which provides accuracy and flexibility in matching the signals statistics compared to other fading models. The complexity which arises in the calculations of the RCPC codes parameters is significantly reduced by using equivalent convolutional codes. Results show that the use of high-rate code allows for bandwidth efficiency and at the same time does not severely degrades the system performance. It is also shown that the MMSE-based system outperforms the conventional ZF-based system especially in the low Eb/N0 region and in severe fading conditions.


Rectangular and Circular Antenna Design on Thick Substrate

Abstract: Millimeter wave technology being an emerging area is still very undeveloped. A substantial research needs to be done in this area as its applications are numerous. In the present endeavor, a rectangular patch antenna is designed on thick substrate and simulated using SONNET software, also a novel analysis technique is developed for circular patch antenna for millimeter wave frequency. The antenna is designed at 39 GHz on thick substrate and has been analyzed and simulated.The results of the theoretical analysis are in good agreement with the simulated results.


Mutual Coupling Reduction in Two-Dimensional Array of Microstrip Antennas Using Concave Rectangular Patches

Abstract: Using concave rectangular patches, a new solution to reduce mutual coupling and return loss in two-dimensional array of microstrip antennas is proposed. The effect of width and length concavity on mutual coupling and return loss is studied. Also, the patch parameters as well as the amounts of width and length concavity are optimized using an enhanced genetic algorithm. Simulation results show that the resulting array antenna has low amounts of mutual coupling and return loss.


Image transmission over OFDM channel with rate allocation scheme and minimum peak-toaverage power ratio

Abstract: This paper proposes new scheme for efficient rate allocation in conjunction with reducing peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. Modification of the set partitioning in hierarchical trees (SPIHT) image coder is proposed to generate four different groups of bit-stream relative to its significances. The significant bits, the sign bits, the set bits and the refinement bits are transmitted in four different groups. The proposed method for reducing the PAPR utilizes twice the unequal error protection (UEP), using the Read-Solomon codes (RS), in conjunction with bit-rate allocation and selective interleaving to provide minimum PAPR. The output bit-stream from the source code (SPIHT) will be started by the most significant types of bits (first group of bits). The optimal unequal error protection (UEP) of the four groups is proposed based on the channel destortion. The proposed structure provides significant improvement in bit error rate (BER) performance. Performed computer simulations have shown that the proposed scheme outperform the performance of most of the recent PAPR reduction techniques in most cases. Moreover, the simulation results indicate that the proposed scheme provides significantly better PSNR performance in comparison to well-known robust coding schemes.


Performance Evaluation of Two-Stage Shared FDL Optical Packet Switch using Contention Resolution Scheme with Packet Releasing Priority

Abstract: This paper proposes a two-stage optical packet switch with second stage of recirculate switch of FDL to reduce the number of the FDL used in the switch for contention resolution. The contention resolution scheme with priority in packet releasing from FDL is tested in the two-stage switch for performance evaluation. Simulation result shows that zero packet loss rate achievable with {\i}< 0.8 for 32x 32 two-stage switch.


Capacity Optimized For Multicarrier OFDM-MIMO Antenna Systems

Abstract: Motivated by MIMO broad-band fading channel model, in this section we deals with the capacity behaviour of wireless MIMO and OFDM based spatial multiplexing systems in broad-band fading environments for the case where the channel is unknown at the transmitter and perfectly known at the receiver. This influence the propagation and system parameters on ergodic capacity, we furthermore demonstrate that, unlike the single-input single-output (SISO) case, delay spread channels may provide advantage over flat-fading channels not only in terms of outage capacity but also in terms of ergodic capacity. Therefore, MIMO delay spread channels will in general provide both higher diversity gain and higher multiplexing gain than MIMO flat-fading channels.


Improving GPS Precision and Processing Time using Parallel and Reduced-Length Wiener Filters

Abstract: Increasing GPS precision at low cost has always been a challenge for the manufacturers of the GPS receivers. This paper proposes the use of a Wiener filter for increasing precision in substitution of traditional GPS/INS fusion systems, which require expensive inertial systems. In this paper, we first implement and compare three GPS signal processing schemes: a Kalman filter, a neural network and a Wiener filter and compare them in terms of precision and the processing time. To further reduce the processing time of Wiener filter, we propose parallel and reduced-length implementations. Finally, we calculate the sampling frequency that would be required in every Wiener scheme in order to obtain the same total processing time as the Kalman filter and the neural network.


Imprvoing QoS of all-IP Generation of Pre-WiMax Networks Using Delay-Jitter Model

Abstract: The topic of this paper is the evaluation of QoS parameters in live Pre-Wimax environments. The main contribution is the validation of an analytical delay-jitter behavior model. These models can be used in optimization algorithms in order to provide opportunistic and reliable all-IP networks. It allows understanding the impact of the jitter constraints on the throughput and packet loss in wireless systems. However, we show that the real-time QoS requirements of real-time and interactive services can be avoided to a large degree by controlling only the packet delay-jitter in a fixed and mobile environment. The QoS metrics have been computed from live measurements in a Pre-Wimax realistic environment (Toulouse/Blagnac Airport).


Holographic Projection Technology: The World is Changing

Abstract: This research papers examines the new technology of Holographic Projections. It highlights the importance and need of this technology and how it represents the new wave in the future of technology and communications, the different application of the technology, the fields of life it will dramatically affect including business, education, telecommunication and healthcare. The paper also discusses the future of holographic technology and how it will prevail in the coming years highlighting how it will also affect and reshape many other fields of life, technologies and businesses.


Analysis of Beaulieu Pulse Shaping Family Based FIR Filter for WCDMA

Abstract: The analysis and simulation of transmit and receive pulse shaping filter is an important aspect of digital wireless communication since it has a direct effect on error probabilities. Pulse shaping for wireless communication over time as well as frequency selective channels is the need of hour for 3G and 4G systems. The pulse shaping filter is a useful means to shape the signal spectrum and avoid interferences. Basically digital filters are used to modify the characteristics of signal in time and frequency domain and have been recognized as primary digital signal processing operations.


Simulink based VoIP Analysis

Abstract: Voice communication over internet not be possible without a reliable data network, this was first available when distributed network topologies were used in conjunction with data packets. Early network used single centre node network in which a single workstation (Server) is responsible for the communication. This posed problems as if there was a fault with the centre node, (workstation) nothing would work. This problem was solved by the distributed system in which reliability increases by spreading the load between many nodes. The idea of packet switching & distributed network were combined, this combination were increased reliability, speed & responsible for voice communication over internet, Voice-over-IP (VoIP)These data packets travel through a packet-switched network such as the Internet and arrive at their destination where they are decompressed using a compatible Codec (audio coder/decoder) and converted back to analogue audio. This paper deals with the Simulink architecture for VoIP network.


Novel method for planar microstrip antenna matching impedance

Abstract: Because all microstrip antennas have to be matched to the standard generator impedance or load, the input impedance matching method for antenna is particularly important. In this paper a new methodology in achieving matching impedance of a planar microstrip antenna for wireless application is described. The method is based on embedding an Interdigital capacitor. The fine results obtained by using a microstrip Interdigital capacitor for matching antenna impedance led to an efficient method to improve array antenna performance. In fact, a substantial saving on the whole surfaces as well as enhancement of the gain, the directivity and the power radiated was achieved.


To Optimally Design Microstrip Nonuniform Transmission Lines as Lowpass Filters

Abstract: A method is proposed to optimally design the Microstrip Nonuniform Transmission Line (MNTLs) as lowpass filters. Some electrical and physical restrictions are used to design MNTLs. To optimally design the MNTLs, their strip width is expanded as truncated Fourier series, firstly. Then, the optimum values of the coefficients of the series are obtained through an optimization approach. The performance of the proposed structure is studied by design and fabrication of two lowpass filters of cutoff frequency 2.0 GHz.


Implementation of Handoff through wireless access point Techniques

Abstract: Handoff has become an inevitable part of wireless cellular communication, Soon users will carry small portable handheld devices which will incorporate the computer, phone, camera, GPS, personal control module etc. This paper proposes a new scheme to deal with seam less roaming and reduce failed handoffs. The simulation is done using software called Qualnet meant for wireless communication. The results clearly indicate the advantages of this new scheme.


Mechanism for Learning Object retrieval supporting adaptivity

Abstract: In today\^as world designing adaptable course material requires new technical knowledge which involves a need for a uniform protocol that allows organizing resources with emphasis on quality and Learning. This can be achieved by bundling the resources in a known and prescribed fashion called Learning objects. Learning Objects are composed of two aspects namely "Learning" and "Object". The Learning aspect of Learning objects refers to Education. Since Education is a process so the primary aim of learning objects tends to be facilitating acquisition, assessment and conversion of content into Learning objects while fostering the assimilation of these Learning objects into learning modules and instruction. The Object part of Learning objects relates to the Digital Electronic format of the resources i.e. to say that it deals with the physical resource that forms the Learning objects. The objects in LOs are analogous to objects used in object-oriented modeling (OOM). The analogy helps visualize how LOs will be packaged, processed and transported across the digital library as well as utilized in course building. OOM concepts such as encapsulation, classification, polymorphism, inheritance and reuse can be borrowed to describe the operations on LOs in the digital library. Thus, the aim of this paper is threefolds. Firstly, to discuss the background of this research and the concept of Learning Objects. Secondly, to provide a framework for adaptive mechanism for the retrieval of Learning Objects and thirdly to highlight the benefits that this new proposed framework shall bring.


A Study on the Interactive "HOPSCOTCH" Game for the Children Using Computer Music Techniques

Abstract: "Hopscotch" is a world-wide game for children to play since the times in the ancient Roman Empire and China. Here we present a study mainly focused on the research and discussion of the application on the children's well-know edutainment via the physical interactive design to provide the sensing of the times for the conventional hopscotch, which is a new type of experiment for the technology aided edutainment. The innovated hopscotch music game involves the sound samples of various animals and the characters of cartoon, and the algorithmic composition via the development of the music technology based interactive game, to gradually make the children perceive the world of digits, sound, and music. It can guide the growing children's personality and character from disorder into clarity. Furthermore, the traditional teaching materials can be improved via the implementation of the electrical sensing devices, electrical I/O module, and the computer music program Max/MSP, to integrate the interactive computer music with the interactive and immersive soundscapes composition, and the teaching tool with educational gaming is completely accomplished eventually.


An Interactive Zoo Guide: A Case Study of Collaborative Learning

Abstract: Real Industry Projects and team work can have a great impact on student learning but providing these activities requires significant commitment from academics. It requires several years planning implementing to create a collaborative learning environment that mimics the real world ICT (Information and Communication Technology) industry workplace. In this project, staff from all the three faculties, namely the Faculty of Health, Engineering and Science, Faculty of Arts, Education and Human Development, and Faculty of Business and Law in higher education work together to establish a detailed project management plan and to develop the unit guidelines for participating students. The proposed project brings together students from business, multimedia and computer science degrees studying their three project-based units within each faculty to work on a relatively large IT project with our industry partner, Melbourne Zoo. This paper presents one multimedia software project accomplished by one of the multi-discipline student project teams. The project was called 'Interactive ZooOz Guide' and developed on a GPS-enabled PDA device in 2007. The developed program allows its users to navigate through the Zoo via an interactive map and provides multimedia information of animals on hotspots at the 'Big Cats' section of the Zoo so that it enriches user experience at the Zoo. A recent development in zoo applications is also reviewed. This paper is also intended to encourage academia to break boundaries to enhance students' learning beyond classroom.


Building a Data Warehouse for National Social Security Fund of the Republic of Tunisia

Abstract: The amounts of data available to decision makers are increasingly important, given the network availability, low cost storage and diversity of applications. To maximize the potential of these data within the National Social Security Fund (NSSF) in Tunisia, we have built a data warehouse as a multidimensional database, cleaned, homogenized, historicized and consolidated. We used Oracle Warehouse Builder to extract, transform and load the source data into the Data Warehouse, by applying the KDD process. We have implemented the Data Warehouse as an Oracle OLAP. The knowledge extraction has been performed using the Oracle Discoverer tool. This allowed users to take maximum advantage of knowledge as a regular report or as ad hoc queries. We started by implementing the main topic for this public institution, accounting for the movements of insured persons. The great success that has followed the completion of this work has encouraged the NSSF to complete the achievement of other topics of interest within the NSSF. We suggest in the near future to use Multidimensional Data Mining to extract hidden knowledge and that are not predictable by the OLAP.


Developing E-Learning Materials for Software Development Course

Abstract: Software Development is a core second-year course currently offered to undergraduate students at Victoria University at its five local and international campuses. The project aims to redesign the existing course curriculum to support student-centred teaching and learning. It is intended to provide a learning context in which learners can reflect on new material, discuss their tentative understandings with others, actively search for new information, develop skills in communication and collaboration, and build conceptual connections to their existing knowledge base. The key feature of the cross-campus curriculum innovation is the use of Blackboard, short for Blackboard Learning System, to assist in course content organization and online delivery. A well-defined and integrated case study is used throughout the course to provide realistic practical experience of software development. It allows students to take control of their own learning while at the same time providing support to those students who have particular learning difficulties. In this paper, the developed curriculum and the learning outcome are described. The e-Learning material and various Blackboard tools used for teaching and learning activities are presented. Finally, conclusion is drawn from classroom experience.


Expressiveness of a Provenance-Enabled Authorization Logic

Abstract: In distributed environments, access control decisions depend on statements of multiple agents rather than only one central trusted party. However, existing policy languages put few emphasis on authorization provenances. The capability of managing these provenances is important and useful in various security areas such as computer auditing and authorization recycling. Based on our previously proposed logic, we present several case studies of this logic. By doing this, we show its expressiveness and usefulness in security arena.


On cycles through two arcs in strong multipartite tournaments

Abstract: A multipartite tournament is an orientation of a complete $c$-partite graph. In [L. Volkmann, A remark on cycles through an arc in strongly connected multipartite tournaments, Appl. Math. Lett. 20 (2007) 1148--1150], Volkmann proved that a strongly connected $c$-partite tournament with $c \ge 3$ contains an arc that belongs to a directed cycle of length $m$ for every $m \in \{3, 4, \ldots, c\}$. He also conjectured the existence of three arcs with this property. In this note, we prove the existence of two such arcs.


Variational Program Inference

Abstract: We introduce a framework for representing a variety of interesting problems as inference over the execution of probabilistic model programs. We represent a "solution" to such a problem as a guide program which runs alongside the model program and influences the model program's random choices, leading the model program to sample from a different distribution than from its priors. Ideally the guide program influences the model program to sample from the posteriors given the evidence. We show how the KL- divergence between the true posterior distribution and the distribution induced by the guided model program can be efficiently estimated (up to an additive constant) by sampling multiple executions of the guided model program. In addition, we show how to use the guide program as a proposal distribution in importance sampling to statistically prove lower bounds on the probability of the evidence and on the probability of a hypothesis and the evidence. We can use the quotient of these two bounds as an estimate of the conditional probability of the hypothesis given the evidence. We thus turn the inference problem into a heuristic search for better guide programs.


An Enhanced Search Technique for Managing Partial Coverage and Free Riding in P2P Networks

Abstract: This paper presents a Q-learning based scheme for managing the partial coverage problem and the ill-effects of free riding in unstructured P2P networks. Based on various parameter values collected during query routing, reward for the actions are computed and these rewards are used for updating the corresponding Q-values of peers. Thus, the routing is done through only nodes which have shown high performance in the past. Simulation experiments are conducted in several times and the results are plotted. Results show that the proposed scheme effectively manages free riders, generates high hit ratio, reduces network traffic and manages partial coverage problem.


`Q-Feed' - An Effective Solution for the Free-riding Problem in Unstructured P2P Networks

Abstract: This paper presents a solution for reducing the ill effects of free-riders in decentralised unstructured P2P networks. An autonomous replication scheme is proposed to improve the availability and enhance system performance. Q-learning is widely employed in different situations to improve the accuracy in decision making by each peer. Based on the performance of neighbours of a peer, every neighbour is awarded different levels of ranks. At the same time a low-performing node is allowed to improve its rank in different ways. Simulation results show that Q-learning based free riding control mechanism effectively limits the services received by free-riders and also encourages the low-performing neighbours to improve their position. The popular files are autonomously replicated to nodes possessing required parameters. Due to this improvement of quantity of popular files, free riders are given opportunity to lift their position for active participation in the network for sharing files. Q-feed effectively manages queries from free riders and reduces network traffic significantly