Affective Ludology, Flow and Immersion in a First- Person Shooter: Measurement of Player Experience

Abstract: Gameplay research about experiential phenomena is a challenging undertaking, given the variety of experiences that gamers encounter when playing and which currently do not have a formal taxonomy, such as flow, immersion, boredom, and fun. These informal terms require a scientific explanation. Ludologists also acknowledge the need to understand cognition, emotion, and goal- oriented behavior of players from a psychological perspective by establishing rigorous methodologies. This paper builds upon and extends prior work in an area for which we would like to coin the term "affective ludology." The area is concerned with the affective measurement of player-game interaction. The experimental study reported here investigated different traits of gameplay experience using subjective (i.e., questionnaires) and objective (i.e., psychophysiological) measures. Participants played three Half-Life 2 game level design modifications while measures such as electromyography (EMG), electrodermal activity (EDA) were taken and questionnaire responses were collected. A level designed for combat-oriented flow experience demonstrated significant high-arousal positive affect emotions. This method shows that emotional patterns emerge from different level designs, which has great potential for providing real-time emotional profiles of gameplay that may be generated together with self- reported subjective player experience descriptions.


From Playability to a Hierarchical Game Usability Model

Abstract: This paper presents a brief review of current game usability models. This leads to the conception of a high-level game development-centered usability model that integrates current usability approaches in game industry and game research.


Trends and Techniques in Visual Gaze Analysis

Abstract: Visualizing gaze data is an effective way for the quick interpretation of eye tracking results. This paper presents a study investigation benefits and limitations of visual gaze analysis among eye tracking professionals and researchers. The results were used to create a tool for visual gaze analysis within a Master's project.


Gameplay experience in a gaze interaction game

Abstract: Assessing gameplay experience for gaze interaction games is a challenging task. For this study, a gaze interaction Half-Life 2 game modification was created that allowed eye tracking control. The mod was deployed during an experiment at Dreamhack 2007, where participants had to play with gaze navigation and afterwards rate their gameplay experience. The results show low tension and negative affects scores on the gameplay experience questionnaire as well as high positive challenge, immersion and flow ratings. The correlation between spatial presence and immersion for gaze interaction was high and yields further investigation. It is concluded that gameplay experience can be correctly assessed with the methodology presented in this paper.


On Memory Accelerated Signal Processing within Software Defined Radios

Abstract: Since J. Mitola's work in 1992, Software Defined Radios (SDRs) have been quite a hot topic in wireless systems research. Though many notable achievements were reported in the field, the scarcity of computational power on general purpose CPUs has always constrained their wide adoption in production environments. If conveniently applied within an SDR context, classical concepts known in computer science as space/time tradeoffs can be extremely helpful when trying to mitigate this problem. Inspired by and building on those concepts, this paper presents a novel SDR implementation technique which we call Memory Acceleration (MA) that makes extensive use of the memory resources available on a general purpose computing system, in order to accelerate signal computation. MA can provide substantial acceleration factors when applied to conventional SDRs without reducing their peculiar flexibility. As a practical proof of this, an example of MA applied in the real world to the ETSI DVB-T Viterbi decoder is provided. Actually MA is shown able to provide, when applied to such Viterbi decoder, an acceleration factor of 10.4x, with no impact on error correction performances of the decoder and by making no use of any other typical performance enhancement techniques such as low level (Assembler) programming or parallel computation, which though remain compatible with MA. Opportunity for extending the MA approach to the entire radio system, thus implementing what we call a Memory-Based Software Defined Radio (MB-SDR) is finally considered and discussed.


A hybrid decision approach for the association problem in heterogeneous networks

Abstract: The area of networking games has had a growing impact on wireless networks. This reflects the recognition in the important scaling advantages that the service providers can benefit from by increasing the autonomy of mobiles in decision making. This may however result in inefficiencies that are inherent to equilibria in non-cooperative games. Due to the concern for efficiency, centralized protocols keep being considered and compared to decentralized ones. From the point of view of the network architecture, this implies the co-existence of network-centric and terminal centric radio resource management schemes. Instead of taking part within the debate among the supporters of each solution, we propose in this paper hybrid schemes where the wireless users are assisted in their decisions by the network that broadcasts aggregated load information. We derive the utilities related to the Quality of Service (QoS) perceived by the users and develop a Bayesian framework to obtain the equilibria. Numerical results illustrate the advantages of using our hybrid game framework in an association problem in a network composed of HSDPA and 3G LTE systems.


Approximation Algorithms for Campaign Management

Abstract: We study electoral campaign management scenarios in which an external party can buy votes, i.e., pay the voters to promote its preferred candidate in their preference rankings. The external party's goal is to make its preferred candidate a winner while paying as little as possible. We describe a 2-approximation algorithm for this problem for a large class of electoral systems known as scoring rules. Our result holds even for weighted voters, and has applications for campaign management in commercial settings. We also give approximation algorithms for our problem for two Condorcet-consistent rules, namely, the Copeland rule and maximin.


An Oblivious Spanning Tree for Buy-at-Bulk Network Design Problems

Abstract: We consider the problem of constructing a single spanning tree for the single-source buy-at-bulk network design problem for doubling-dimension graphs. We compute a spanning tree to route a set of demands (or data) along a graph to or from a designated root node. The demands could be aggregated at (or symmetrically distributed to) intermediate nodes where the fusion-cost is specified by a non-negative concave function $f$. We describe a novel approach for developing an oblivious spanning tree in the sense that it is independent of the number of data sources (or demands) and cost function at intermediate nodes. To our knowledge, this is the first paper to propose a single spanning tree solution to this problem (as opposed to multiple overlay trees). There has been no prior work where the tree is oblivious to both the fusion cost function and the set of sources (demands). We present a deterministic, polynomial-time algorithm for constructing a spanning tree in low doubling graphs that guarantees $\log^{3}D\cdot\log n$-approximation over the optimal cost, where $D$ is the diameter of the graph and $n$ the total number of nodes. With constant fusion-cost function our spanning tree gives a $O(\log^3 D)$-approximation for every Steiner tree to the root.


A Spatial Crypto Technique for Secure Data Transmission

Abstract: This paper presents a spatial encryption technique for secured transmission of data in networks. The algorithm is designed to break the ciphered data packets into multiple data which are to be packaged into a spatial template. A secure and efficient mechanism is provided to convey the information that is necessary for obtaining the original data at the receiver-end from its parts in the packets. An authentication code (MAC) is also used to ensure authenticity of every packet.


Facial Expression Representation and Recognition Using 2DHLDA, Gabor Wavelets, and Ensemble Learning

Abstract: In this paper, a novel method for representation and recognition of the facial expressions in two-dimensional image sequences is presented. We apply a variation of two-dimensional heteroscedastic linear discriminant analysis (2DHLDA) algorithm, as an efficient dimensionality reduction technique, to Gabor representation of the input sequence. 2DHLDA is an extension of the two-dimensional linear discriminant analysis (2DLDA) approach and it removes the equal within-class covariance. By applying 2DHLDA in two directions, we eliminate the correlations between both image columns and image rows. Then, we perform a one-dimensional LDA on the new features. This combined method can alleviate the small sample size problem and instability encountered by HLDA. Also, employing both geometric and appearance features and using an ensemble learning scheme based on data fusion, we create a classifier which can efficiently classify the facial expressions. The proposed method is robust to illumination changes and it can properly represent temporal information as well as subtle changes in facial muscles. We provide experiments on Cohn-Kanade database that show the superiority of the proposed method. KEYWORDS: two-dimensional heteroscedastic linear discriminant analysis (2DHLDA), subspace learning, facial expression analysis, Gabor wavelets, ensemble learning.


Estimating Self-Sustainability in Peer-to-Peer Swarming Systems

Abstract: Peer-to-peer swarming is one of the \emph{de facto} solutions for distributed content dissemination in today's Internet. By leveraging resources provided by clients, swarming systems reduce the load on and costs to publishers. However, there is a limit to how much cost savings can be gained from swarming; for example, for unpopular content peers will always depend on the publisher in order to complete their downloads. In this paper, we investigate this dependence. For this purpose, we propose a new metric, namely \emph{swarm self-sustainability}. A swarm is referred to as self-sustaining if all its blocks are collectively held by peers; the self-sustainability of a swarm is the fraction of time in which the swarm is self-sustaining. We pose the following question: how does the self-sustainability of a swarm vary as a function of content popularity, the service capacity of the users, and the size of the file? We present a model to answer the posed question. We then propose efficient solution methods to compute self-sustainability. The accuracy of our estimates is validated against simulation. Finally, we also provide closed-form expressions for the fraction of time that a given number of blocks is collectively held by peers.


CONCISE: Compressed 'n' Composable Integer Set

Abstract: Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas, such as data warehousing, information retrieval, and data mining, to cite a few. However, bitmaps usually use a large storage space, thus requiring compression. Nevertheless, there is a space-time tradeoff among compression schemes. The Word Aligned Hybrid (WAH) bitmap compression trades some space to allow for bitwise operations without first decompressing bitmaps. WAH has been recognized as the most efficient scheme in terms of computation time. In this paper we present CONCISE (Compressed 'n' Composable Integer Set), a new scheme that enjoys significatively better performances than those of WAH. In particular, when compared to WAH, our algorithm is able to reduce the required memory up to 50%, by having similar or better performance in terms of computation time. Further, we show that CONCISE can be efficiently used to manipulate bitmaps representing sets of integral numbers in lieu of well-known data structures such as arrays, lists, hashtables, and self-balancing binary search trees. Extensive experiments over synthetic data show the effectiveness of our approach.


A Faster Routing Scheme for Stationary Wireless Sensor Networks - A Hybrid Approach

Abstract: A wireless sensor network consists of light-weight, low power, small size sensor nodes. Routing in wireless sensor networks is a demanding task. This demand has led to a number of routing protocols which efficiently utilize the limited resources available at the sensor nodes. Most of these protocols are either based on single hop routing or multi hop routing and typically find the minimum energy path without addressing other issues such as time delay in delivering a packet, load balancing, and redundancy of data. Response time is very critical in environment monitoring sensor networks where typically the sensors are stationary and transmit data to a base station or a sink node. In this paper a faster load balancing routing protocol based on location with a hybrid approach is proposed.


Shadowing Effects on Routing Protocol of Multihop Ad Hoc Networks

Abstract: Two-ray ground reflection model has been widely used as the propagation model to investigate the performance of an ad hoc network. But two-ray model is too simple to represent a real world network. A more realistic model namely shadowing propagation model has been used in this investigation. Under shadowing propagation model, a mobile node may receive a packet at a signal level that is below a required threshold level. This low signal level affects the routing protocol as well as the medium access control protocol of a network. An analytical model has been presented in this paper to investigate the shadowing effects on the network performance. The analytical model has been verified via simulation results. Simulation results show that the performance of a network becomes very poor if shadowing propagation model is used in compare to the simple two-ray model. Two solutions have also been proposed in this paper to overcome the effects of shadowing. One solution is a physical layer solution and the other one is a Medium Access Control (MAC) layer solution. Simulation results show that these two solutions reduce the shadowing effect and improve network performance.


Restricted Common Superstring and Restricted Common Supersequence

Abstract: The {\em shortest common superstring} and the {\em shortest common supersequence} are two well studied problems having a wide range of applications. In this paper we consider both problems with resource constraints, denoted as the Restricted Common Superstring (shortly \textit{RCSstr}) problem and the Restricted Common Supersequence (shortly \textit{RCSseq}). In the \textit{RCSstr} (\textit{RCSseq}) problem we are given a set $S$ of $n$ strings, $s_1$, $s_2$, $\ldots$, $s_n$, and a multiset $t = \{t_1, t_2, \dots, t_m\}$, and the goal is to find a permutation $\pi : \{1, \dots, m\} \to \{1, \dots, m\}$ to maximize the number of strings in $S$ that are substrings (subsequences) of $\pi(t) = t_{\pi(1)}t_{\pi(2)}...t_{\pi(m)}$ (we call this ordering of the multiset, $\pi(t)$, a permutation of $t$). We first show that in its most general setting the \textit{RCSstr} problem is {\em NP-complete} and hard to approximate within a factor of $n^{1-\epsilon}$, for any $\epsilon > 0$, unless P = NP. Afterwards, we present two separate reductions to show that the \textit{RCSstr} problem remains NP-Hard even in the case where the elements of $t$ are drawn from a binary alphabet or for the case where all input strings are of length two. We then present some approximation results for several variants of the \textit{RCSstr} problem. In the second part of this paper, we turn to the \textit{RCSseq} problem, where we present some hardness results, tight lower bounds and approximation algorithms.


On the parity complexity measures of Boolean functions

Abstract: The parity decision tree model extends the decision tree model by allowing the computation of a parity function in one step. We prove that the deterministic parity decision tree complexity of any Boolean function is polynomially related to the non-deterministic complexity of the function or its complement. We also show that they are polynomially related to an analogue of the block sensitivity. We further study parity decision trees in their relations with an intermediate variant of the decision trees, as well as with communication complexity.


User-driven applications

Abstract: User-driven applications are the programs, in which the full control is given to the users. Designers of such programs are responsible only for developing an instrument for solving some task, but they do not enforce users to work with this instrument according with the predefined scenario. Users' control of the applications means that only users decide at any moment WHAT, WHEN, and HOW must appear on the screen. Such applications can be constructed only on the basis of moveable / resizable elements. Programs, based on such elements, have very interesting features and open absolutely new possibilities. This article describes the design of the user-driven applications and shows the consequences of switching to such type of programs on the samples from different areas.


Embedding Secret Data in HTML Web Page

Abstract: In this paper, we suggest a novel data hiding technique in an HTML Web page. HTML Tags are case insensitive and hence an alphabet in lowercase and one in uppercase present inside an HTML tag are interpreted in the same manner by the browser,i.e., change in case in an web page is imperceptible to the browser. We basically exploit this redundancy and use it to embed secret data inside an web page, with no changes visible to the user of the web page, so that he can not even suspect about the data hiding. The embedded data can be recovered by viewing the source of the HTML page. This technique can easily be extended to embed secret message inside any piece of source-code where the standard interpreter of that language is case-insensitive.


Analysis, Interpretation, and Recognition of Facial Action Units and Expressions Using Neuro-Fuzzy Modeling

Abstract: In this paper an accurate real-time sequence-based system for representation, recognition, interpretation, and analysis of the facial action units (AUs) and expressions is presented. Our system has the following characteristics: 1) employing adaptive-network-based fuzzy inference systems (ANFIS) and temporal information, we developed a classification scheme based on neuro-fuzzy modeling of the AU intensity, which is robust to intensity variations, 2) using both geometric and appearance-based features, and applying efficient dimension reduction techniques, our system is robust to illumination changes and it can represent the subtle changes as well as temporal information involved in formation of the facial expressions, and 3) by continuous values of intensity and employing top-down hierarchical rule-based classifiers, we can develop accurate human-interpretable AU-to-expression converters. Extensive experiments on Cohn-Kanade database show the superiority of the proposed method, in comparison with support vector machines, hidden Markov models, and neural network classifiers. Keywords: biased discriminant analysis (BDA), classifier design and evaluation, facial action units (AUs), hybrid learning, neuro-fuzzy modeling.


Superior Exploration-Exploitation Balance with Quantum-Inspired Hadamard Walks

Abstract: This paper extends the analogies employed in the development of quantum-inspired evolutionary algorithms by proposing quantum-inspired Hadamard walks, called QHW. A novel quantum-inspired evolutionary algorithm, called HQEA, for solving combinatorial optimization problems, is also proposed. The novelty of HQEA lies in it's incorporation of QHW Remote Search and QHW Local Search - the quantum equivalents of classical mutation and local search, that this paper defines. The intuitive reasoning behind this approach, and the exploration-exploitation balance thus occurring is explained. From the results of the experiments carried out on the 0,1-knapsack problem, HQEA performs significantly better than a conventional genetic algorithm, CGA, and two quantum-inspired evolutionary algorithms - QEA and NQEA, in terms of convergence speed and accuracy.


Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network

Abstract: Facial Action Coding System consists of 44 action units (AUs) and more than 7000 combinations. Hidden Markov models (HMMs) classifier has been used successfully to recognize facial action units (AUs) and expressions due to its ability to deal with AU dynamics. However, a separate HMM is necessary for each single AU and each AU combination. Since combinations of AU numbering in thousands, a more efficient method will be needed. In this paper an accurate real-time sequence-based system for representation and recognition of facial AUs is presented. Our system has the following characteristics: 1) employing a mixture of HMMs and neural network, we develop a novel accurate classifier, which can deal with AU dynamics, recognize subtle changes, and it is also robust to intensity variations, 2) although we use an HMM for each single AU only, by employing a neural network we can recognize each single and combination AU, and 3) using both geometric and appearance-based features, and applying efficient dimension reduction techniques, our system is robust to illumination changes and it can represent the temporal information involved in formation of the facial expressions. Extensive experiments on Cohn-Kanade database show the superiority of the proposed method, in comparison with other classifiers. Keywords: classifier design and evaluation, data fusion, facial action units (AUs), hidden Markov models (HMMs), neural network (NN).


Multilinear Biased Discriminant Analysis: A Novel Method for Facial Action Unit Representation

Abstract: In this paper a novel efficient method for representation of facial action units by encoding an image sequence as a fourth-order tensor is presented. The multilinear tensor-based extension of the biased discriminant analysis (BDA) algorithm, called multilinear biased discriminant analysis (MBDA), is first proposed. Then, we apply the MBDA and two-dimensional BDA (2DBDA) algorithms, as the dimensionality reduction techniques, to Gabor representations and the geometric features of the input image sequence respectively. The proposed scheme can deal with the asymmetry between positive and negative samples as well as curse of dimensionality dilemma. Extensive experiments on Cohn-Kanade database show the superiority of the proposed method for representation of the subtle changes and the temporal information involved in formation of the facial expressions. As an accurate tool, this representation can be applied to many areas such as recognition of spontaneous and deliberate facial expressions, multi modal/media human computer interaction and lie detection efforts.


A New Lower Bound on the Maximum Number of Satisfied Clauses in Max-SAT and its Algorithmic Applications

Abstract: A pair of unit clauses is called conflicting if it is of the form $(x)$, $(\bar{x})$. A CNF formula is unit-conflict free (UCF) if it contains no pair of conflicting unit clauses. Lieberherr and Specker (J. ACM 28, 1981) showed that for each UCF CNF formula with $m$ clauses we can simultaneously satisfy at least $\pp m$ clauses, where $\pp =(\sqrt{5}-1)/2$. We improve the Lieberherr-Specker bound by showing that for each UCF CNF formula $F$ with $m$ clauses we can find, in polynomial time, a subformula $F'$ with $m'$ clauses such that we can simultaneously satisfy at least $\pp m+(1-\pp)m'+(2-3\pp)n"/2$ clauses (in $F$), where $n"$ is the number of variables in $F$ which are not in $F'$. We consider two parameterized versions of MAX-SAT, where the parameter is the number of satisfied clauses above the bounds $m/2$ and $m(\sqrt{5}-1)/2$. The former bound is tight for general formulas, and the later is tight for UCF formulas. Mahajan and Raman (J. Algorithms 31, 1999) showed that every instance of the first parameterized problem can be transformed, in polynomial time, into an equivalent one with at most $6k+3$ variables and $10k$ clauses. We improve this to $4k$ variables and $(2\sqrt{5}+4)k$ clauses. Mahajan and Raman conjectured that the second parameterized problem is fixed-parameter tractable (FPT). We show that the problem is indeed FPT by describing a polynomial-time algorithm that transforms any problem instance into an equivalent one with at most $(7+3\sqrt{5})k$ variables. Our results are obtained using our improvement of the Lieberherr-Specker bound above.


Querying for the Largest Empty Geometric Object in a Desired Location

Abstract: We study new types of geometric query problems defined as follows: given a geometric set $P$, preprocess it such that given a query point $q$, the location of the largest circle that does not contain any member of $P$, but contains $q$ can be reported efficiently. The geometric sets we consider for $P$ are boundaries of convex and simple polygons, and point sets. While we primarily focus on circles as the desired shape, we also briefly discuss empty rectangles in the context of point sets.


Using Rough Set and Support Vector Machine for Network Intrusion Detection

Abstract: The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict the behaviors of users. Then these behaviors will be considered an attack or a normal behavior. Though IDS has been developed for many years, the large number of return alert messages makes managers maintain system inefficiently. In this paper, we use RST (Rough Set Theory) and SVM (Support Vector Machine) to detect intrusions. First, RST is used to preprocess the data and reduce the dimensions. Next, the features were selected by RST will be sent to SVM model to learn and test respectively. The method is effective to decrease the space density of data. The experiments will compare the results with different methods and show RST and SVM schema could improve the false positive rate and accuracy.


Tools and techniques for Network Forensics

Abstract: Network forensics deals with the capture, recording and analysis of network events in order to discover evidential information about the source of security attacks in a court of law. This paper discusses the different tools and techniques available to conduct network forensics. Some of the tools discussed include: eMailTrackerPro to identify the physical location of an email sender; Web Historian to find the duration of each visit and the files uploaded and downloaded from the visited website; packet sniffers like Etherea to capture and analyze the data exchanged among the different computers in the network. The second half of the paper presents a survey of different IP traceback techniques like packet marking that help a forensic investigator to identify the true sources of the attacking IP packets. We also discuss the use of Honeypots and Honeynets that gather intelligence about the enemy and the tools and tactics of network intruders.


Encryption Quality Analysis and Security Evaluation of CAST-128 Algorithm and its Modified Version using Digital Images

Abstract: this paper demonstrates analysis of well known block cipher CAST-128 and its modified version using avalanche criterion and other tests namely encryption quality, correlation coefficient, histogram analysis and key sensitivity tests.


A Comparison between Memetic algorithm and Genetic algorithm for the cryptanalysis of Simplified Data Encryption Standard algorithm

Abstract: Genetic algorithms are a population-based Meta heuristics. They have been successfully applied to many optimization problems. However, premature convergence is an inherent characteristic of such classical genetic algorithms that makes them incapable of searching numerous solutions of the problem domain. A memetic algorithm is an extension of the traditional genetic algorithm. It uses a local search technique to reduce the likelihood of the premature convergence. The cryptanalysis of simplified data encryption standard can be formulated as NP-Hard combinatorial problem. In this paper, a comparison between memetic algorithm and genetic algorithm were made in order to investigate the performance for the cryptanalysis on simplified data encryption standard problems(SDES). The methods were tested and various experimental results show that memetic algorithm performs better than the genetic algorithms for such type of NP-Hard combinatorial problem. This paper represents our first effort toward efficient memetic algorithm for the cryptanalysis of SDES.


A New Cluster-based Wormhole Intrusion detection algorithm for Mobile Ad-Hoc Networks

Abstract: In multi-hop wireless systems, the need for cooperation among nodes to relay each other's packets exposes them to a wide range of security attacks. A particularly devastating attack is the wormhole attack, where a malicious node records control traffic at one location and tunnels it to another compromised node, possibly far away, which replays it locally. Routing security in ad hoc networks is often equated with strong and feasible node authentication and lightweight cryptography. Unfortunately, the wormhole attack can hardly be defeated by crypto graphical measures, as wormhole attackers do not create separate packets. They simply replay packets already existing on the network, which pass the cryptographic checks. Existing works on wormhole detection have often focused on detection using specialized hardware, such as directional antennas, etc. In this paper, we present a cluster based counter-measure for the wormhole attack, that alleviates these drawbacks and efficiently mitigates the wormhole attack in MANET. Simulation results on MATLab exhibit the effectiveness of the proposed algorithm in detecting wormhole attacks.


Iterative method for improvement of coding and decryption

Abstract: Cryptographic check values (digital signatures, MACs and H-MACs) are useful only if they are free of errors. For that reason all of errors in cryptographic check values should be corrected after the transmission over a noisy channel before their verification is performed. Soft Input Decryption is a method of combining SISO convolutional decoding and decrypting of cryptographic check values to improve the correction of errors in themselves. If Soft Input Decryption is successful, i.e. all wrong bit of a cryptographic check value are corrected, these bit are sent as feedback information to the channel decoder for a next iteration. The bit of the next iteration are corrected by channel decoding followed by another Soft Input Decryption. Iterative Soft Input Decryption uses interleaved blocks. If one block can be corrected by Soft Input Decryption, the decoding of the interleaved block is improved (serial scheme). If Soft Input Decryption is applied on both blocks and one of the blocks can be corrected, the corrected block is used for an improved decoding of the other block (parallel scheme). Both schemes show significant coding gains compared to convolutional decoding without iterative Soft Input Decryption.


A new key establishment scheme for wireless sensor networks

Abstract: Traditional key management techniques, such as public key cryptography or key distribution center (e.g., Kerberos), are often not effective for wireless sensor networks for the serious limitations in terms of computational power, energy supply, network bandwidth. In order to balance the security and efficiency, we propose a new scheme by employing LU Composition techniques for mutual authenticated pairwise key establishment and integrating LU Matrix with Elliptic Curve Diffie-Hellman for anonymous pathkey establishment. At the meantime, it is able to achieve efficient group key agreement and management. Analysis shows that the new scheme has better performance and provides authenticity and anonymity for sensor to establish multiple kinds of keys, compared with previous related works.


Dynamic IDP Signature processing by fast elimination using DFA

Abstract: Intrusion Detection & Prevention Systems generally aims at detecting / preventing attacks against Information systems and networks. The basic task of IDPS is to monitor network & system traffic for any malicious packets/patterns and hence to prevent any unwarranted incidents which leads the systems to insecure state. The monitoring is done by checking each packet for its validity against the signatures formulated for identified vulnerabilities. Since, signatures are the heart & soul of an Intrusion Detection and Prevention System (IDPS), we, in this paper, discuss two methodologies we adapted in our research effort to improve the current Intrusion Detection and Prevention (IDP) systems. The first methodology RUDRAA is for formulating, verifying & validating the potential signatures to be used with IDPS. The second methodology DSP-FED is aimed at processing the signatures in less time with our proposed fast elimination method using DFA. The research objectives of this project are 1) To formulate & process potential IPS signatures to be used with Intrusion prevention system. 2) To propose a DFA based approach for signature processing which, upon a pattern match, could process the signatures faster else could eliminate it efficiently if not matched


Effect of Inter Packet Delay in performance analysis of coexistence heterogeneous Wireless Packet Networks

Abstract: As the explosive growth of the ISM band usage continues, there are many scenarios where different systems operate in the same place at the same time. One of growing concerns is the coexistence of heterogeneous wireless network systems. For the successful deployment of mission-critical systems such as wireless sensor networks, it is required to provide a solution for the coexistence. In this paper, we propose a new scheme using inter packet delay for the coexistence of IEEE 802.15.4 LRWPAN and IEEE 802.11b WLAN. To evaluate the effectiveness of the proposed scheme, measurement and simulation study are conducted using Qualnet 4.5 simulation software. The simulation results show that the proposed scheme is effective in performance improvement for coexistence network of IEEE 802.15.4 for various topologies.


Clustered Hierarchy in Sensor Networks: Performance and Security

Abstract: Many papers have been proposed in order to increase the wireless sensor networks performance; This kind of network has limited resources, where the energy in each sensor came from a small battery that sometime is hard to be replaced or recharged. Transmission energy is the most concern part where the higher energy consumption takes place. Clustered hierarchy has been proposed in many papers; in most cases, it provides the network with better performance than other protocols. In our paper, first we discuss some of techniques, relates to this protocol, that have been proposed for energy efficiency; some of them were proposed to provide the network with more security level. Our proposal then suggests some modifications to some of these techniques to provide the network with more energy saving that should lead to high performance; also we apply our technique on an existing one that proposed to increase the security level of cluster sensor networks.


Quantum Three-Pass protocol: Key distribution using quantum superposition states

Abstract: This letter proposes a novel key distribution protocol with no key exchange in advance, which is secure as the BB84 quantum key distribution protocol. Our protocol utilizes a photon in superposition state for single-bit data transmission instead of a classical electrical/optical signal. The security of this protocol relies on the fact, that the arbitrary quantum state cannot be cloned, known as the no-cloning theorem. This protocol can be implemented with current technologies.


Intelligent Detection System framework using Mobile agents

Abstract: An intrusion detection system framework using mobile agents is a layered framework mechanism designed to support heterogeneous network environments to identify intruders at its best. Traditional computer misuse detection techniques can identify known attacks efficiently, but perform very poorly in other cases. Anomaly detection has the potential to detect unknown attacks; however, it is a very challenging task since its aim is to detect unknown attacks without any priori knowledge about specific intrusions. This technology is still at its early stage. The objective of this paper is that the system can detect anomalous user activity. Existing research in this area focuses either on user activity or on program operation but not on both simultaneously. In this paper, an attempt to look at both concurrently is presented. Based on an intrusion detection framework [1], a novel user anomaly detection system has been implemented and conducted several intrusion detection experiments in a simulated environment by analyzing user activity and program operation activities. The proposed framework is a layered framework, which is designed to satisfy the core purpose of IDS, and allows detecting the intrusion as quickly as possible with available data using mobile agents. This framework was mainly designed to provide security for the network using mobile agent mechanisms to add mobility features to monitor the user processes from different computational systems. The experimental results have shown that the system can detect anomalous user activity effectively.


On Generation of Firewall Log Status Reporter (SRr) Using Perl

Abstract: Computer System Administration and Network Administration are few such areas where Practical Extraction Reporting Language (Perl) has robust utilization these days apart from Bioinformatics. The key role of a System/Network Administrator is to monitor log files. Log file are updated every day. To scan the summary of large log files and to quickly determine if there is anything wrong with the server or network we develop a Firewall Log Status Reporter (SRr). SRr helps to generate the reports based on the parameters of interest. SRr provides the facility to admin to generate the individual firewall report or all reports in one go. By scrutinizing the results of the reports admin can trace how many times a particular request has been made from which source to which destination and can track the errors easily. Perl scripts can be seen as the UNIX script replacement in future arena and SRr is one development with the same hope that we can believe in. SRr is a generalized and customizable utility completely written in Perl and may be used for text mining and data mining application in Bioinformatics research and development too.


Quantum Key Distribution (QKD) and Commodity Security Protocols: Introduction and Integration

Abstract: We present an overview of quantum key distribution (QKD), a secure key exchange method based on the quantum laws of physics rather than computational complexity. We also provide an overview of the two most widely used commodity security protocols, IPsec and TLS. Pursuing a key exchange model, we propose how QKD could be integrated into these security applications. For such a QKD integration we propose a support layer that provides a set of common QKD services between the QKD protocol and the security applications


The Isomorphism Problem for omega-Automatic Trees

Abstract: The main result of this paper is that the isomorphism for omega-automatic trees of finite height is at least has hard as second-order arithmetic and therefore not analytical. This strengthens a recent result by Hjorth, Khoussainov, Montalban, and Nies showing that the isomorphism problem for omega-automatic structures is not $\Sigma^1_2$. Moreover, assuming the continuum hypothesis CH, we can show that the isomorphism problem for omega-automatic trees of finite height is recursively equivalent with second-order arithmetic. On the way to our main results, we show lower and upper bounds for the isomorphism problem for omega-automatic trees of every finite height: (i) It is decidable ($\Pi^0_1$-complete, resp,) for height 1 (2, resp.), (ii) $\Pi^1_1$-hard and in $\Pi^1_2$ for height 3, and (iii) $\Pi^1_{n-3}$- and $\Sigma^1_{n-3}$-hard and in $\Pi^1_{2n-4}$ (assuming CH) for all n > 3. All proofs are elementary and do not rely on theorems from set theory.


Exact Ramsey Theory: Green-Tao numbers and SAT

Abstract: We consider the links between Ramsey theory in the integers, based on van der Waerden's theorem, and (boolean, CNF) SAT solving. We aim at using the problems from exact Ramsey theory, concerned with computing Ramsey-type numbers, as a rich source of test problems, where especially methods for solving hard problems can be developed. In order to control the growth of the problem instances, we introduce "transversal extensions" as a natural way of constructing mixed parameter tuples (k_1, ..., k_m) for van-der-Waerden-like numbers N(k_1, ..., k_m), such that the growth of these numbers is guaranteed to be linear. Based on Green-Tao's theorem we introduce the "Green-Tao numbers" grt(k_1, ..., k_m), which in a sense combine the strict structure of van der Waerden problems with the (pseudo-)randomness of the distribution of prime numbers. Using standard SAT solvers (look-ahead, conflict-driven, and local search) we determine the basic values. It turns out that already for this single form of Ramsey-type problems, when considering the best-performing solvers a wide variety of solver types is covered. For m > 2 the problems are non-boolean, and we introduce the "generic translation scheme", which offers an infinite variety of translations ("encodings") and covers the known methods. In most cases the special instance called "nested translation" proved to be far superior.


Effects of component-subscription network topology on large-scale data centre performance scaling

Abstract: Modern large-scale date centres, such as those used for cloud computing service provision, are becoming ever-larger as the operators of those data centres seek to maximise the benefits from economies of scale. With these increases in size comes a growth in system complexity, which is usually problematic. There is an increased desire for automated "self-star" configuration, management, and failure-recovery of the data-centre infrastructure, but many traditional techniques scale much worse than linearly as the number of nodes to be managed increases. As the number of nodes in a median-sized data-centre looks set to increase by two or three orders of magnitude in coming decades, it seems reasonable to attempt to explore and understand the scaling properties of the data-centre middleware before such data-centres are constructed. In [1] we presented SPECI, a simulator that predicts aspects of large-scale data-centre middleware performance, concentrating on the influence of status changes such as policy updates or routine node failures. [...]. In [1] we used a first-approximation assumption that such subscriptions are distributed wholly at random across the data centre. In this present paper, we explore the effects of introducing more realistic constraints to the structure of the internal network of subscriptions. We contrast the original results [...] exploring the effects of making the data-centre's subscription network have a regular lattice-like structure, and also semi-random network structures resulting from parameterised network generation functions that create "small-world" and "scale-free" networks. We show that for distributed middleware topologies, the structure and distribution of tasks carried out in the data centre can significantly influence the performance overhead imposed by the middleware.


Measuring and Synthesizing Systems in Probabilistic Environments

Abstract: Often one has a preference order among the different systems that satisfy a given specification. Under a probabilistic assumption about the possible inputs, such a preference order is naturally expressed by a weighted automaton, which assigns to each word a value, such that a system is preferred if it generates a higher expected value. We solve the following optimal-synthesis problem: given an omega-regular specification, a Markov chain that describes the distribution of inputs, and a weighted automaton that measures how well a system satisfies the given specification under the given input assumption, synthesize a system that optimizes the measured value. For safety specifications and measures given by mean-payoff automata, the optimal-synthesis problem amounts to finding a strategy in a Markov decision process (MDP) that is optimal for a long-run average reward objective, which can be done in polynomial time. For general omega-regular specifications, the solution rests on a new, polynomial-time algorithm for computing optimal strategies in MDPs with mean-payoff parity objectives. Our algorithm generates optimal strategies consisting of two memoryless strategies and a counter. This counter is in general not bounded. To obtain a finite-state system, we show how to construct an \epsilon-optimal strategy with a bounded counter for any \epsilon>0. We also show how to decide in polynomial time if we can construct an optimal finite-state system (i.e., a system without a counter) for a given specification. We have implemented our approach in a tool that takes qualitative and quantitative specifications and automatically constructs a system that satisfies the qualitative specification and optimizes the quantitative specification, if such a system exists. We present experimental results showing optimal systems that were generated in this way.


Extended Two-Dimensional PCA for Efficient Face Representation and Recognition

Abstract: In this paper a novel method called Extended Two-Dimensional PCA (E2DPCA) is proposed which is an extension to the original 2DPCA. We state that the covariance matrix of 2DPCA is equivalent to the average of the main diagonal of the covariance matrix of PCA. This implies that 2DPCA eliminates some covariance information that can be useful for recognition. E2DPCA instead of just using the main diagonal considers a radius of r diagonals around it and expands the averaging so as to include the covariance information within those diagonals. The parameter r unifies PCA and 2DPCA. r = 1 produces the covariance of 2DPCA, r = n that of PCA. Hence, by controlling r it is possible to control the trade-offs between recognition accuracy and energy compression (fewer coefficients), and between training and recognition complexity. Experiments on ORL face database show improvement in both recognition accuracy and recognition time over the original 2DPCA.


Integrating identity-based cryptography in IMS service authentication

Abstract: Nowadays, the IP Multimedia Subsystem (IMS) is a promising research field. Many ongoing works related to the security and the performances of its employment are presented to the research community. Although, the security and data privacy aspects are very important in the IMS global objectives, they observe little attention so far. Secure access to multimedia services is based on SIP and HTTP digest on top of IMS architecture. The standard deploys AKA-MD5 for the terminal authentication. The third Generation Partnership Project (3GPP) provided Generic Bootstrapping Architecture (GBA) to authenticate the subscriber before accessing multimedia services over HTTP. In this paper, we propose a new IMS Service Authentication scheme using Identity Based cryptography (IBC). This new scheme will lead to better performances when there are simultaneous authentication requests using Identity-based Batch Verification. We analyzed the security of our new protocol and we presented a performance evaluation of its cryptographic operations


Agent Based Trust Management Model Based on Weight Value Model for Online Auctions

Abstract: This paper is aimed at the stipulations which arise in the traditional online auctions as a result of various anomalies in the reputation and trust calculation mechanism. We try to improve the scalability and efficiency of the online auctions by providing efficient trust management methodology considering several factors into consideration. A comparison between the performance of the auctions system with and without the agent methodology is done with good results


Text/Graphics Separation for Business Card Images for Mobile Devices

Abstract: Separation of the text regions from background texture and graphics is an important step of any optical character recognition sytem for the images containg both texts and graphics. In this paper, we have presented a novel text/graphics separation technique for business card images captured with a cell-phone camera. At first, the background is eliminated at a coarse level based on intensity variance. This makes the foreground components distinct from each other. Then the non-text components are removed using various characteristic features of text and graphics. Finally, the text regions are skew corrected and binarized for further processing. Experimenting with business card images of various resolutions, we have found an optimum performance of 98.54% with 0.75 MP images, that takes 0.17 seconds processing time and 1.1 MB peak memory on a moderately powerful computer (DualCore 1.73 GHz Processor, 1 GB RAM, 1 MB L2 Cache). The developed technique is computationally efficient and consumes low memory so as to be applicable on mobile devices.


Cryptanalysis of a more efficient and secure dynamic id-based remote user authentication scheme

Abstract: In 2004, Das, Saxena and Gulati proposed a dynamic ID-based remote user authentication scheme which has many advantage such as no verifier table, user freedom to choose and change password and so on. However the subsequent papers have shown that this scheme is completely insecure and vulnerable to many attacks. Since then many schemes with improvements to Das et al's scheme has been proposed but each has its pros and cons. Recently Yan-yan Wang et al. have proposed a scheme to overcome security weaknesses of Das et al.'s scheme. However this scheme too is vulnerable to various security attacks such as password guessing attack, masquerading attack, denial of service attack.


PSIM: A tool for analysis of device pairing methods

Abstract: Wireless networks are a common place nowadays and almost all of the modern devices support wireless communication in some form. These networks differ from more traditional computing systems due to the ad-hoc and spontaneous nature of interactions among devices. These systems are prone to security risks, such as eavesdropping and require different techniques as compared to traditional security mechanisms. Recently, secure device pairing in wireless environments has got substantial attention from many researchers. As a result, a significant set of techniques and protocols have been proposed to deal with this issue. Some of these techniques consider devices equipped with infrared, laser, ultrasound transceivers or 802.11 network interface cards; while others require embedded accelerometers, cameras and/or LEDs, displays, microphones and/or speakers. However, many of the proposed techniques or protocols have not been implemented at all; while others are implemented and evaluated in a stand-alone manner without being compared with other related work [1]. We believe that it is because of the lack of specialized tools that provide a common platform to test the pairing methods. As a consequence, we designed such a tool. In this paper, we are presenting design and development of the Pairing Simulator (PSim) that can be used to perform the analysis of device pairing methods.


Data security in mobile devices by geo locking

Abstract: In this paper we present a way of hiding the data in mobile devices from being compromised. We use two level data hiding technique, where in its first level data is encrypted and stored in special records and the second level being a typical password protection scheme. The second level is for secure access of information from the device. In the first level, encryption of the data is done using the location coordinates as key. Location Coordinates are rounded up figures of longitude and latitude information. In the second phase the password entry differs from conventional schemes. Here we have used the patterns of traditional Rangoli for specifying the password and gaining access, thus minimising the chances of data leak in hostile situations. The proposed structure would be a better trade off in comparison with the previous models which use Bio Metric authentication -- a relatively costly way of authentication.


Performance evaluation of a new route optimization technique for mobile IP

Abstract: Mobile ip (mip) is an internet protocol that allows mobile nodes to have continuous network connectivity to the internet without changing their ip addresses while moving to other networks. The packets sent from correspondent node (cn) to a mobile node (mn) go first through the mobile node's home agent (ha), then the ha tunnels them to the mn's foreign network. One of the main problems in the original mip is the triangle routing problem. Triangle routing problem appears when the indirect path between cn and mn through the ha is longer than the direct path. This paper proposes a new technique to improve the performance of the original mip during the handoff. The proposed technique reduces the delay, the packet loss and the registration time for all the packets transferred between the cn and the mn. In this technique, tunneling occurs at two levels above the ha in a hierarchical network. To show the effectiveness of the proposed technique, it is compared with the original mip and another technique for solving the same problem in which tunneling occurs at one level above the ha. Simulation results presented in this paper are based on the ns2 mobility software on linux platform. The simulations results show that our proposed technique achieves better performance than the others, considering the packet delay, the packet losses during handoffs and the registration time, in different scenarios for the location of the mn with respect to the ha and fas.


Security properties in an open peer-to-peer network

Abstract: This paper proposes to address new requirements of confidentiality, integrity and availability properties fitting to peer-to-peer domains of resources. The enforcement of security properties in an open peer-topeer network remains an open problem as the literature have mainly proposed contribution on availability of resources and anonymity of users. That paper proposes a novel architecture that eases the administration of a peer-to-peer network. It considers a network of safe peer-to-peer clients in the sense that it is a commune client software that is shared by all the participants to cope with the sharing of various resources associated with different security requirements. However, our proposal deals with possible malicious peers that attempt to compromise the requested security properties. Despite the safety of an open peer-to-peer network cannot be formally guaranteed, since a end user has privileges on the target host, our solution provides several advanced security enforcement. First, it enables to formally define the requested security properties of the various shared resources. Second, it evaluates the trust and the reputation of the requesting peer by sending challenges that test the fairness of its peer-to-peer security policy. Moreover, it proposes an advanced Mandatory Access Control that enforces the required peer-to-peer security properties through an automatic projection of the requested properties onto SELinux policies. Thus, the SELinux system of the requesting peer is automatically configured with respect to the required peer-to-peer security properties.


A security framework for SOA applications in mobile environment

Abstract: A Rapid evolution of mobile technologies has led to the development of more sophisticated mobile devices with better storage, processing and transmission power. These factors enable support to many types of application but also give rise to a necessity to find a model of service development. Actually, SOA (Service Oriented Architecture) is a good option to support application development. This paper presents a framework that allows the development of SOA based application in mobile environment. The objective of the framework is to give developers with tools for provision of services in this environment with the necessary security characteristics.


Abstract: This article has been withdrawn by arXiv admins because it contains plagiarized content from International Conference on Computer Networks and Security (ICCNS 2008, September 27-28, 2008): "Securing AODV for MANETs using Message Digest with Secret Key", by Sunil J. Soni and Prashant B. Swadas.


From Holant To #CSP And Back: Dichotomy For Holant$^c$ Problems

Abstract: We explore the intricate interdependent relationship among counting problems, considered from three frameworks for such problems: Holant Problems, counting CSP and weighted H-colorings. We consider these problems for general complex valued functions that take boolean inputs. We show that results from one framework can be used to derive results in another, and this happens in both directions. Holographic reductions discover an underlying unity, which is only revealed when these counting problems are investigated in the complex domain $\mathbb{C}$. We prove three complexity dichotomy theorems, leading to a general theorem for Holant$^c$ problems. This is the natural class of Holant problems where one can assign constants 0 or 1. More specifically, given any signature grid on $G=(V,E)$ over a set ${\mathscr F}$ of symmetric functions, we completely classify the complexity to be in P or #P-hard, according to ${\mathscr F}$, of \[\sum_{\sigma: E \rightarrow \{0,1\}} \prod_{v\in V} f_v(\sigma\mid_{E(v)}),\] where $f_v \in {\mathscr F} \cup \{{\bf 0}, {\bf 1}\}$ ({\bf 0}, {\bf 1} are the unary constant 0, 1 functions). Not only is holographic reduction the main tool, but also the final dichotomy can be only naturally stated in the language of holographic transformations. The proof goes through another dichotomy theorem on boolean complex weighted #CSP.


Nepotistic Relationships in Twitter and their Impact on Rank Prestige Algorithms

Abstract: Micro-blogging services such as Twitter allow anyone to publish anything, anytime. Needless to say, many of the available contents can be diminished as babble or spam. However, given the number and diversity of users, some valuable pieces of information should arise from the stream of tweets. Thus, such services can develop into valuable sources of up-to-date information (the so-called real-time web) provided a way to find the most relevant/trustworthy/authoritative users is available. Hence, this makes a highly pertinent question for which graph centrality methods can provide an answer. In this paper the author offers a comprehensive survey of feasible algorithms for ranking users in social networks, he examines their vulnerabilities to linking malpractice in such networks, and suggests an objective criterion against which to compare such algorithms. Additionally, he suggests a first step towards "desensitizing" prestige algorithms against cheating by spammers and other abusive users.


A Separation of NP and coNP in Multiparty Communication Complexity

Abstract: We prove that NP differs from coNP and coNP is not a subset of MA in the number-on-forehead model of multiparty communication complexity for up to k = (1-\epsilon)log(n) players, where \epsilon>0 is any constant. Specifically, we construct a function F with co-nondeterministic complexity O(log(n)) and Merlin-Arthur complexity n^{\Omega(1)}. The problem was open for k > 2.


On the Complexity of Local Search for Weighted Standard Set Problems

Abstract: In this paper, we study the complexity of computing locally optimal solutions for weighted versions of standard set problems such as SetCover, SetPacking, and many more. For our investigation, we use the framework of PLS, as defined in Johnson et al., [JPY88]. We show that for most of these problems, computing a locally optimal solution is already PLS-complete for a simple neighborhood of size one. For the local search versions of weighted SetPacking and SetCover, we derive tight bounds for a simple neighborhood of size two. To the best of our knowledge, these are one of the very few PLS results about local search for weighted standard set problems.


On building minimal automaton for subset matching queries

Abstract: We address the problem of building an index for a set $D$ of $n$ strings, where each string location is a subset of some finite integer alphabet of size $\sigma$, so that we can answer efficiently if a given simple query string (where each string location is a single symbol) $p$ occurs in the set. That is, we need to efficiently find a string $d \in D$ such that $p[i] \in d[i]$ for every $i$. We show how to build such index in $O(n^{\log_{\sigma/\Delta}(\sigma)}\log(n))$ average time, where $\Delta$ is the average size of the subsets. Our methods have applications e.g.\ in computational biology (haplotype inference) and music information retrieval.


Spying the World from your Laptop -- Identifying and Profiling Content Providers and Big Downloaders in BitTorrent

Abstract: This paper presents a set of exploits an adversary can use to continuously spy on most BitTorrent users of the Internet from a single machine and for a long period of time. Using these exploits for a period of 103 days, we collected 148 million IPs downloading 2 billion copies of contents. We identify the IP address of the content providers for 70% of the BitTorrent contents we spied on. We show that a few content providers inject most contents into BitTorrent and that those content providers are located in foreign data centers. We also show that an adversary can compromise the privacy of any peer in BitTorrent and identify the big downloaders that we define as the peers who subscribe to a large number of contents. This infringement on users' privacy poses a significant impediment to the legal adoption of BitTorrent.


Indian policeman's dilemma: A game theoretic model

Abstract: This paper focuses on a one person game called Indian policeman's dilemma (IPD). It represents the internal conflict between emotion and profession of a typical Indian police officer. We have 'split' the game to be played independently by different personality modules of the same player. Each module then appears as an independent individual player of the game. None of the players knows the exact payoff values of any of the others. Only greater than or less than type of inequalities among the payoff values across the players are to be inferred probabilistically. There are two Nash equilibrium (NE) points in this game signifying two completely opposing behavior by the policeman involved. With the help of the probabilistic inequalities probable propensities of the different behaviors have been determined. The model underscores the need for new surveys and data generation. A design of one such survey to measure professionalism of the police personnel has been outlined.


The Automatic Synthesis of Linear Ranking Functions: The Complete Unabridged Version

Abstract: The classical technique for proving termination of a generic sequential computer program involves the synthesis of a ranking function for each loop of the program. Linear ranking functions are particularly interesting because many terminating loops admit one and algorithms exist to automatically synthesize it. In this paper we present two such algorithms: one based on work dated 1991 by Sohn and Van Gelder; the other, due to Podelski and Rybalchenko, dated 2004. Remarkably, while the two algorithms will synthesize a linear ranking function under exactly the same set of conditions, the former is mostly unknown to the community of termination analysis and its general applicability has never been put forward before the present paper. In this paper we thoroughly justify both algorithms, we prove their correctness, we compare their worst-case complexity and experimentally evaluate their efficiency, and we present an open-source implementation of them that will make it very easy to include termination-analysis capabilities in automatic program verifiers.


The Complexity of Partition Functions on Hermitian Matrices

Abstract: Partition functions of certain classes of "spin glass" models in statistical physics show strong connections to combinatorial graph invariants. Also known as homomorphism functions they allow for the representation of many such invariants, for example, the number of independent sets of a graph or the number nowhere zero k-flows. Contributing to recent developments on the complexity of partition functions we study the complexity of partition functions with complex values. These functions are usually determined by a square matrix A and it was shown by Goldberg, Grohe, Jerrum, and Thurley that for each real-valued symmetric matrix, the corresponding partition function is either polynomial time computable or #P-hard. Extending this result, we give a complete description of the complexity of partition functions definable by Hermitian matrices. These can also be classified into polynomial time computable and #P-hard ones. Although the criterion for polynomial time computability is not describable in a single line, we give a clear account of it in terms of structures associated with Abelian groups.


Strong Fault-Tolerance for Self-Assembly with Fuzzy Temperature

Abstract: We consider the problem of fault-tolerance in nanoscale algorithmic self-assembly. We employ a variant of Winfree's abstract Tile Assembly Model (aTAM), the two-handed aTAM, in which square "tiles" -- a model of molecules constructed from DNA for the purpose of engineering self-assembled nanostructures -- aggregate according to specific binding sites of varying strengths, and in which large aggregations of tiles may attach to each other, in contrast to the seeded aTAM, in which tiles aggregate one at a time to a single specially-designated "seed" assembly. We focus on a major cause of errors in tile-based self-assembly: that of unintended growth due to "weak" strength-1 bonds, which if allowed to persist, may be stabilized by subsequent attachment of neighboring tiles in the sense that at least energy 2 is now required to break apart the resulting assembly; i.e., the errant assembly is stable at temperature 2. We study a common self-assembly benchmark problem, that of assembling an n x n square using O(log n) unique tile types, under the two-handed model of self-assembly. Our main result achieves a much stronger notion of fault-tolerance than those achieved previously. Arbitrary strength-1 growth is allowed (i.e., the temperature is "fuzzy" and may drift from 2 to 1 for arbitrarily long); however, any assembly that grows sufficiently to become stable at temperature 2 is guaranteed to assemble at temperature 2 into the correct final assembly of an n x n square. In other words, errors due to insufficient attachment, which is the cause of errors studied in earlier papers on fault-tolerance, are prevented absolutely in our main construction, rather than only with high probability and for sufficiently small structures, as in previous fault-tolerance studies.


The Graph Traversal Pattern

Abstract: A graph is a structure composed of a set of vertices (i.e.nodes, dots) connected to one another by a set of edges (i.e.links, lines). The concept of a graph has been around since the late 19$^\text{th}$ century, however, only in recent decades has there been a strong resurgence in both theoretical and applied graph research in mathematics, physics, and computer science. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval model. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph databases make use of index-free, local traversals. This article discusses the graph traversal pattern and its use in computing.


Bounded Reachability for Temporal Logic over Constraint Systems

Abstract: We present CLTLB(D), an extension of PLTLB (PLTL with both past and future operators) augmented with atomic formulae built over a constraint system D. Even for decidable constraint systems, satisfiability and Model Checking problem of such logic can be undecidable. We introduce suitable restrictions and assumptions that are shown to make the satisfiability problem for the extended logic decidable. Moreover for a large class of constraint systems we propose an encoding that realize an effective decision procedure for the Bounded Reachability problem.


Unified Compression-Based Acceleration of Edit-Distance Computation

Abstract: The edit distance problem is a classical fundamental problem in computer science in general, and in combinatorial pattern matching in particular. The standard dynamic programming solution for this problem computes the edit-distance between a pair of strings of total length O(N) in O(N^2) time. To this date, this quadratic upper-bound has never been substantially improved for general strings. However, there are known techniques for breaking this bound in case the strings are known to compress well under a particular compression scheme. The basic idea is to first compress the strings, and then to compute the edit distance between the compressed strings. As it turns out, practically all known o(N^2) edit-distance algorithms work, in some sense, under the same paradigm described above. It is therefore natural to ask whether there is a single edit-distance algorithm that works for strings which are compressed under any compression scheme. A rephrasing of this question is to ask whether a single algorithm can exploit the compressibility properties of strings under any compression method, even if each string is compressed using a different compression. In this paper we set out to answer this question by using straight line programs. These provide a generic platform for representing many popular compression schemes including the LZ-family, Run-Length Encoding, Byte-Pair Encoding, and dictionary methods. For two strings of total length N having straight-line program representations of total size n, we present an algorithm running in O(nN log(N/n)) time for computing the edit-distance of these two strings under any rational scoring function, and an O(n^{2/3}N^{4/3}) time algorithm for arbitrary scoring functions. Our new result, while providing a signi cant speed up for highly compressible strings, does not surpass the quadratic time bound even in the worst case scenario.


A Deterministic Algorithm for the Vertex Connectivity Survivable Network Design Problem

Abstract: In the vertex connectivity survivable network design problem we are given an undirected graph G = (V,E) and connectivity requirement r(u,v) for each pair of vertices u,v. We are also given a cost function on the set of edges. Our goal is to find the minimum cost subset of edges such that for every pair (u,v) of vertices we have r(u,v) vertex disjoint paths in the graph induced by the chosen edges. Recently, Chuzhoy and Khanna presented a randomized algorithm that achieves a factor of O(k^3 log n) for this problem where k is the maximum connectivity requirement. In this paper we derandomize their algorithm to get a deterministic O(k^3 log n) factor algorithm. Another problem of interest is the single source version of the problem, where there is a special vertex s and all non-zero connectivity requirements must involve s. We also give a deterministic O(k^2 log n) algorithm for this problem.


Liberalizing Dependency

Abstract: The dependency core calculus (DCC), a simple extension of the computational lambda calculus, captures a common notion of dependency that arises in many programming language settings. This notion of dependency is closely related to the notion of information flow in security; it is sensitive not only to data dependencies that cause explicit flows, but also to control dependencies that cause implicit flows. In this paper, we study variants of DCC in which the data and control dependencies are decoupled. This allows us to consider settings where a weaker notion of dependency---one that restricts only explicit flows---may usefully coexist with DCC's stronger notion of dependency. In particular, we show how strong, noninterference-based security may be reconciled with weak, trace-based security within the same system, enhancing soundness of the latter and completeness of the former.


Regularized Richardson-Lucy Algorithm for Sparse Reconstruction of Poissonian Images

Abstract: Restoration of digital images from their degraded measurements has always been a problem of great theoretical and practical importance in numerous applications of imaging sciences. A specific solution to the problem of image restoration is generally determined by the nature of degradation phenomenon as well as by the statistical properties of measurement noises. The present study is concerned with the case in which the images of interest are corrupted by convolutional blurs and Poisson noises. To deal with such problems, there exists a range of solution methods which are based on the principles originating from the fixed-point algorithm of Richardson and Lucy (RL). In this paper, we provide conceptual and experimental proof that such methods tend to converge to sparse solutions, which makes them applicable only to those images which can be represented by a relatively small number of non-zero samples in the spatial domain. Unfortunately, the set of such images is relatively small, which restricts the applicability of RL-type methods. On the other hand, virtually all practical images admit sparse representations in the domain of a properly designed linear transform. To take advantage of this fact, it is therefore tempting to modify the RL algorithm so as to make it recover representation coefficients, rather than the values of their associated image. Such modification is introduced in this paper. Apart from the generality of its assumptions, the proposed method is also superior to many established reconstruction approaches in terms of estimation accuracy and computational complexity. This and other conclusions of this study are validated through a series of numerical experiments.


Multi-Shift de Bruijn Sequence

Abstract: A (non-circular) de Bruijn sequence w of order n is a word such that every word of length n appears exactly once in w as a factor. In this paper, we generalize the concept to a multi-shift setting: a multi-shift de Bruijn sequence tau(m,n) of shift m and order n is a word such that every word of length n appears exactly once in w as a factor that starts at index im+1 for some integer i>=0. We show the number of the multi-shift de Bruijn sequence tau(m,n) is (a^n)!a^{(m-n)(a^n-1)} for 1<=n<=m and is (a^m!)^{a^{n-m}} for 1<=m<=n, where a=|Sigma|. We provide two algorithms for generating a tau(m,n). The multi-shift de Bruijn sequence is important in solving the Frobenius problem in a free monoid.


Relaxation-based coarsening and multiscale graph organization

Abstract: In this paper we generalize and improve the multiscale organization of graphs by introducing a new measure that quantifies the "closeness" between two nodes. The calculation of the measure is linear in the number of edges in the graph and involves just a small number of relaxation sweeps. A similar notion of distance is then calculated and used at each coarser level. We demonstrate the use of this measure in multiscale methods for several important combinatorial optimization problems and discuss the multiscale graph organization.


Design and Implementation of an Intelligent Educational Model Based on Personality and Learner's Emotion

Abstract: The Personality and emotions are effective parameters in learning process. Thus, virtual learning environments should pay attention to these parameters. In this paper, a new e-learning model is designed and implemented according to these parameters. The Virtual learning environment that is presented here uses two agents: Virtual Tutor Agent (VTA), and Virtual Classmate Agent (VCA). During the learning process and depending on events happening in the environment, learner's emotions are changed. In this situation, learning style should be revised according to the personality traits as well as the learner's current emotions. VTA selects suitable learning style for the learners based on their personality traits. To improve the learning process, the system uses VCA in some of the learning steps. VCA is an intelligent agent and has its own personality. It is designed so that it can present an attractive and real learning environment in interaction with the learner. To recognize the learner's personality, this system uses MBTI test and to obtain emotion values uses OCC model. Finally, the results of system tested in real environments show that considering the human features in interaction with the learner increases learning quality and satisfies the learner.


Signature Recognition using Multi Scale Fourier Descriptor And Wavelet Transform

Abstract: This paper present a novel off-line signature recognition method based on multi scale Fourier Descriptor and wavelet transform . The main steps of constructing a signature recognition system are discussed and experiments on real data sets show that the average error rate can reach 1%. Finally we compare 8 distance measures between feature vectors with respect to the recognition performance. Key words: signature recognition; Fourier Descriptor; Wavelet transform; personal verification


Feature-Based Adaptive Tolerance Tree (FATT): An Efficient Indexing Technique for Content-Based Image Retrieval Using Wavelet Transform

Abstract: This paper introduces a novel indexing and access method, called Feature- Based Adaptive Tolerance Tree (FATT), using wavelet transform is proposed to organize large image data sets efficiently and to support popular image access mechanisms like Content Based Image Retrieval (CBIR).Conventional database systems are designed for managing textual and numerical data and retrieving such data is often based on simple comparisons of text or numerical values. However, this method is no longer adequate for images, since the digital presentation of images does not convey the reality of images. Retrieval of images become difficult when the database is very large. This paper addresses such problems and presents a novel indexing technique, Feature Based Adaptive Tolerance Tree (FATT), which is designed to bring an effective solution especially for indexing large databases. The proposed indexing scheme is then used along with a query by image content, in order to achieve the ultimate goal from the user point of view that is retrieval of all relevant images. FATT indexing technique, features of the image is extracted using 2-dimensional discrete wavelet transform (2DDWT) and index code is generated from the determinant value of the features. Multiresolution analysis technique using 2D-DWT can decompose the image into components at different scales, so that the coarest scale components carry the global approximation information while the finer scale components contain the detailed information. Experimental results show that the FATT outperforms M-tree upto 200%, Slim-tree up to 120% and HCT upto 89%. FATT indexing technique is adopted to increase the efficiently of data storage and retrieval.


Ontology-supported processing of clinical text using medical knowledge integration for multi-label classification of diagnosis coding

Abstract: This paper discusses the knowledge integration of clinical information extracted from distributed medical ontology in order to ameliorate a machine learning-based multi-label coding assignment system. The proposed approach is implemented using a decision tree based cascade hierarchical technique on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding.


Botnet Detection by Monitoring Similar Communication Patterns

Abstract: Botnet is most widespread and occurs commonly in today's cyber attacks, resulting in serious threats to our network assets and organization's properties. Botnets are collections of compromised computers (Bots) which are remotely controlled by its originator (BotMaster) under a common Command-and-Control (C&C) infrastructure. They are used to distribute commands to the Bots for malicious activities such as distributed denial-of-service (DDoS) attacks, spam and phishing. Most of the existing Botnet detection approaches concentrate only on particular Botnet command and control (C&C) protocols (e.g., IRC,HTTP) and structures (e.g., centralized), and can become ineffective as Botnets change their structure and C&C techniques. In this paper at first we provide taxonomy of Botnets C&C channels and evaluate well-known protocols which are being used in each of them. Then we proposed a new general detection framework which currently focuses on P2P based and IRC based Botnets. This proposed framework is based on definition of Botnets. Botnet has been defined as a group of bots that perform similar communication and malicious activity patterns within the same Botnet. The point that distinguishes our proposed detection framework from many other similar works is that there is no need for prior knowledge of Botnets such as Botnet signature.


Lightweight Distance bound Protocol for Low Cost RFID Tags

Abstract: Almost all existing RFID authentication schemes (tag/reader) are vulnerable to relay attacks, because of their inability to estimate the distance to the tag. These attacks are very serious since it can be mounted without the notice of neither the reader nor the tag and cannot be prevented by cryptographic protocols that operate at the application layer. Distance bounding protocols represent a promising way to thwart relay attacks, by measuring the round trip time of short authenticated messages. All the existing distance bounding protocols use random number generator and hash functions at the tag side which make them inapplicable at low cost RFID tags. This paper proposes a lightweight distance bound protocol for low cost RFID tags. The proposed protocol based on modified version of Gossamer mutual authentication protocol. The implementation of the proposed protocol meets the limited abilities of low-cost RFID tags.


Analysis of Empirical Software Effort Estimation Models

Abstract: Reliable effort estimation remains an ongoing challenge to software engineers. Accurate effort estimation is the state of art of software engineering, effort estimation of software is the preliminary phase between the client and the business enterprise. The relationship between the client and the business enterprise begins with the estimation of the software. The credibility of the client to the business enterprise increases with the accurate estimation. Effort estimation often requires generalizing from a small number of historical projects. Generalization from such limited experience is an inherently under constrained problem. Accurate estimation is a complex process because it can be visualized as software effort prediction, as the term indicates prediction never becomes an actual. This work follows the basics of the empirical software effort estimation models. The goal of this paper is to study the empirical software effort estimation. The primary conclusion is that no single technique is best for all situations, and that a careful comparison of the results of several approaches is most likely to produce realistic estimates.


Semi-Automatic Index Tuning: Keeping DBAs in the Loop

Abstract: To obtain good system performance, a DBA must choose a set of indices that is appropriate for the workload. The system can aid in this challenging task by providing recommendations for the index configuration. We propose a new index recommendation technique, termed semi-automatic tuning, that keeps the DBA "in the loop" by generating recommendations that use feedback about the DBA's preferences. The technique also works online, which avoids the limitations of commercial tools that require the workload to be known in advance. The foundation of our approach is the Work Function Algorithm, which can solve a wide variety of online optimization problems with strong competitive guarantees. We present an experimental analysis that validates the benefits of semi-automatic tuning in a wide variety of conditions.


Spectral Methods for Matrices and Tensors

Abstract: While Spectral Methods have long been used for Principal Component Analysis, this survey focusses on work over the last 15 years with three salient features: (i) Spectral methods are useful not only for numerical problems, but also discrete optimization problems (Constraint Optimization Problems - CSP's) like the max. cut problem and similar mathematical considerations underlie both areas. (ii) Spectral methods can be extended to tensors. The theory and algorithms for tensors are not as simple/clean as for matrices, but the survey describes methods for low-rank approximation which extend to tensors. These tensor approximations help us solve Max-$r$-CSP's for $r>2$ as well as numerical tensor problems. (iii) Sampling on the fly plays a prominent role in these methods. A primary result is that for any matrix, a random submatrix of rows/columns picked with probabilities proportional to the squared lengths (of rows/columns), yields estimates of the singular values as well as an approximation to the whole matrix.


A Survey on Preprocessing Methods for Web Usage Data

Abstract: World Wide Web is a huge repository of web pages and links. It provides abundance of information for the Internet users. The growth of web is tremendous as approximately one million pages are added daily. Users' accesses are recorded in web logs. Because of the tremendous usage of web, the web log files are growing at a faster rate and the size is becoming huge. Web data mining is the application of data mining techniques in web data. Web Usage Mining applies mining techniques in log data to extract the behavior of users which is used in various applications like personalized services, adaptive web sites, customer profiling, prefetching, creating attractive web sites etc., Web usage mining consists of three phases preprocessing, pattern discovery and pattern analysis. Web log data is usually noisy and ambiguous and preprocessing is an important process before mining. For discovering patterns sessions are to be constructed efficiently. This paper reviews existing work done in the preprocessing stage. A brief overview of various data mining techniques for discovering patterns, and pattern analysis are discussed. Finally a glimpse of various applications of web usage mining is also presented.


Syntactic Abstraction of B Models to Generate Tests

Abstract: In a model-based testing approach as well as for the verification of properties, B models provide an interesting solution. However, for industrial applications, the size of their state space often makes them hard to handle. To reduce the amount of states, an abstraction function can be used, often combining state variable elimination and domain abstractions of the remaining variables. This paper complements previous results, based on domain abstraction for test generation, by adding a preliminary syntactic abstraction phase, based on variable elimination. We define a syntactic transformation that suppresses some variables from a B event model, in addition to a method that chooses relevant variables according to a test purpose. We propose two methods to compute an abstraction A of an initial model M. The first one computes A as a simulation of M, and the second one computes A as a bisimulation of M. The abstraction process produces a finite state system. We apply this abstraction computation to a Model Based Testing process.


De-anonymizing BitTorrent Users on Tor

Abstract: Some BitTorrent users are running BitTorrent on top of Tor to preserve their privacy. In this extended abstract, we discuss three different attacks to reveal the IP address of BitTorrent users on top of Tor. In addition, we exploit the multiplexing of streams from different applications into the same circuit to link non-BitTorrent applications to revealed IP addresses.


In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

Abstract: The basic idea behind Cloud computing is that resource providers offer elastic resources to end users. In this paper, we intend to answer one key question to the success of Cloud computing: in Cloud, can small or medium-scale scientific computing communities benefit from the economies of scale? Our research contributions are three-fold: first, we propose an enhanced scientific public cloud model (ESP) that encourages small- or medium-scale organizations to rent elastic resources from a public cloud provider; second, on a basis of the ESP model, we design and implement the DawningCloud system that can consolidate heterogeneous scientific workloads on a Cloud site; third, we propose an innovative emulation methodology and perform a comprehensive evaluation. We found that for two typical workloads: high throughput computing (HTC) and many task computing (MTC), DawningCloud saves the resource consumption maximally by 44.5% (HTC) and 72.6% (MTC) for service providers, and saves the total resource consumption maximally by 47.3% for a resource provider with respect to the previous two public Cloud solutions. To this end, we conclude that for typical workloads: HTC and MTC, DawningCloud can enable scientific communities to benefit from the economies of scale of public Clouds.


Provable Secure Identity Based Generalized Signcryption Scheme

Abstract: According to actual needs, generalized signcryption scheme can flexibly work as an encryption scheme, a signature scheme or a signcryption scheme. In this paper, firstly, we give a security model for identity based generalized signcryption which is more complete than existing model. Secondly, we propose an identity based generalized signcryption scheme. Thirdly, we give the security proof of the new scheme in this complete model. Comparing with existing identity based generalized signcryption, the new scheme has less implementation complexity. Moreover, the new scheme has comparable computation complexity with the existing normal signcryption schemes.


Distributed Fault-Tolerant Avionic Systems - A Real-Time Perspective

Abstract: This paper examines the problem of introducing advanced forms of fault-tolerance via reconfiguration into safety-critical avionic systems. This is required to enable increased availability after fault occurrence in distributed integrated avionic systems(compared to static federated systems). The approach taken is to identify a migration path from current architectures to those that incorporate re-configuration to a lesser or greater degree. Other challenges identified include change of the development process; incremental and flexible timing and safety analyses; configurable kernels applicable for safety-critical systems.


A note on Johnson, Minkoff and Phillips' algorithm for the Prize-Collecting Steiner Tree Problem

Abstract: The primal-dual scheme has been used to provide approximation algorithms for many problems. Goemans and Williamson gave a (2-1/(n-1))-approximation for the Prize-Collecting Steiner Tree Problem that runs in O(n^3 log n) time. it applies the primal-dual scheme once for each of the n vertices of the graph. Johnson, Minkoff and Phillips proposed a faster implementation of Goemans and Williamson's algorithm. We give a proof that the approximation ratio of this implementation is exactly 2.


Multi-Unit Auctions: Beyond Roberts

Abstract: We exhibit incentive compatible multi-unit auctions that are not affine maximizers (i.e., are not of the VCG family) and yet approximate the social welfare to within a factor of $1+\epsilon$. For the case of two-item two-bidder auctions we show that these auctions, termed Triage auctions, are the only scalable ones that give an approximation factor better than 2. "Scalable" means that the allocation does not depend on the units in which the valuations are measured. We deduce from this that any scalable computationally-efficient incentive-compatible auction for $m$ items and $n \ge 2$ bidders cannot approximate the social welfare to within a factor better than 2. This is in contrast to arbitrarily good approximations that can be reached under computational constraints alone, and in contrast to the fact that the optimal social welfare can be obtained under incentive constraints alone.


Security Policy Enforcement Through Refinement Process

Abstract: In the area of networks, a common method to enforce a security policy expressed in a high-level language is based on an ad-hoc and manual rewriting process. We argue that it is possible to build a formal link between concrete and abstract terms, which can be dynamically computed from the environment data. In order to progressively introduce configuration data and then simplify the proof obligations, we use the B refinement process. We present a case study modeling a network monitor. This program, described by refinement following the layers of the TCP/IP suite protocol, has to warn for all observed events which do not respect the security policy. To design this model, we use the event-B method because it is suitable for modeling network concepts. This work has been done within the framework of the POTESTAT project, based on the research of network testing methods from a high-level security policy.


Compromising Tor Anonymity Exploiting P2P Information Leakage

Abstract: Privacy of users in P2P networks goes far beyond their current usage and is a fundamental requirement to the adoption of P2P protocols for legal usage. In a climate of cold war between these users and anti-piracy groups, more and more users are moving to anonymizing networks in an attempt to hide their identity. However, when not designed to protect users information, a P2P protocol would leak information that may compromise the identity of its users. In this paper, we first present three attacks targeting BitTorrent users on top of Tor that reveal their real IP addresses. In a second step, we analyze the Tor usage by BitTorrent users and compare it to its usage outside of Tor. Finally, we depict the risks induced by this de-anonymization and show that users' privacy violation goes beyond BitTorrent traffic and contaminates other protocols such as HTTP.


GeneSyst: a Tool to Reason about Behavioral Aspects of B Event Specifications. Application to Security Properties.

Abstract: In this paper, we present a method and a tool to build symbolic labelled transition systems from B specifications. The tool, called GeneSyst, can take into account refinement levels and can visualize the decomposition of abstract states in concrete hierarchical states. The resulting symbolic transition system represents all the behaviors of the initial B event system. So, it can be used to reason about them. We illustrate the use of GeneSyst to check security properties on a model of electronic purse.


Are there any good digraph width measures?

Abstract: Several different measures for digraph width have appeared in the last few years. However, none of them shares all the "nice" properties of treewidth: First, being \emph{algorithmically useful} i.e. admitting polynomial-time algorithms for all $\MS1$-definable problems on digraphs of bounded width. And, second, having nice \emph{structural properties} i.e. being monotone under taking subdigraphs and some form of arc contractions. As for the former, (undirected) $\MS1$ seems to be the least common denominator of all reasonably expressive logical languages on digraphs that can speak about the edge/arc relation on the vertex set.The latter property is a necessary condition for a width measure to be characterizable by some version of the cops-and-robber game characterizing the ordinary treewidth. Our main result is that \emph{any reasonable} algorithmically useful and structurally nice digraph measure cannot be substantially different from the treewidth of the underlying undirected graph. Moreover, we introduce \emph{directed topological minors} and argue that they are the weakest useful notion of minors for digraphs.


Importance of Sources using the Repeated Fusion Method and the Proportional Conflict Redistribution Rules #5 and #6

Abstract: We present in this paper some examples of how to compute by hand the PCR5 fusion rule for three sources, so the reader will better understand its mechanism. We also take into consideration the importance of sources, which is different from the classical discounting of sources.


A Streaming Approximation Algorithm for Klee's Measure Problem

Abstract: The efficient estimation of frequency moments of a data stream in one-pass using limited space and time per item is one of the most fundamental problem in data stream processing. An especially important estimation is to find the number of distinct elements in a data stream, which is generally referred to as the zeroth frequency moment and denoted by $F_0$. In this paper, we consider streams of rectangles defined over a discrete space and the task is to compute the total number of distinct points covered by the rectangles. This is known as the Klee's measure problem in 2 dimensions. We present and analyze a randomized streaming approximation algorithm which gives an $(\epsilon, \delta)$-approximation of $F_0$ for the total area of Klee's measure problem in 2 dimensions. Our algorithm achieves the following complexity bounds: (a) the amortized processing time per rectangle is $O(\frac{1}{\epsilon^4}\log^3 n\log\frac{1}{\delta})$; (b) the space complexity is $O(\frac{1}{\epsilon^2}\log n \log\frac{1}{\delta})$ bits; and (c) the time to answer a query for $F_0$ is $O(\log\frac{1}{\delta})$, respectively. To our knowledge, this is the first streaming approximation for the Klee's measure problem that achieves sub-polynomial bounds.