The B-Skip-List: A Simpler Uniquely Represented Alternative to B-Trees

Abstract: In previous work, the author introduced the B-treap, a uniquely represented B-tree analogue, and proved strong performance guarantees for it. However, the B-treap maintains complex invariants and is very complex to implement. In this paper we introduce the B-skip-list, which has most of the guarantees of the B-treap, but is vastly simpler and easier to implement. Like the B-treap, the B-skip-list may be used to construct strongly history-independent index structures and filesystems; such constructions reveal no information about the historical sequence of operations that led to the current logical state. For example, a uniquely represented filesystem would support the deletion of a file in a way that, in a strong information-theoretic sense, provably removes all evidence that the file ever existed. Like the B-tree, the B-skip-list has depth O(log_B (n)) where B is the block transfer size of the external memory, uses linear space with high probability, and supports efficient one-dimensional range queries.


Software Design Document, Testing, Deployment and Configuration Management of the UUIS--a Team 2 COMP5541-W10 Project Approach

Abstract: The Software Design Document of UUIS describes the prototype design details of the system architecture, database layer, deployment and configuration details as well as test cases produced while working the design and implementation of the prototype. The requirements specification of UUIS are detailed in arXiv:1005.0783.


A Linear-time Algorithm for Sparsification of Unweighted Graphs

Abstract: Given an undirected graph $G$ and an error parameter $\epsilon > 0$, the {\em graph sparsification} problem requires sampling edges in $G$ and giving the sampled edges appropriate weights to obtain a sparse graph $G_{\epsilon}$ with the following property: the weight of every cut in $G_{\epsilon}$ is within a factor of $(1\pm \epsilon)$ of the weight of the corresponding cut in $G$. If $G$ is unweighted, an $O(m\log n)$-time algorithm for constructing $G_{\epsilon}$ with $O(n\log n/\epsilon^2)$ edges in expectation, and an $O(m)$-time algorithm for constructing $G_{\epsilon}$ with $O(n\log^2 n/\epsilon^2)$ edges in expectation have recently been developed (Hariharan-Panigrahi, 2010). In this paper, we improve these results by giving an $O(m)$-time algorithm for constructing $G_{\epsilon}$ with $O(n\log n/\epsilon^2)$ edges in expectation, for unweighted graphs. Our algorithm is optimal in terms of its time complexity; further, no efficient algorithm is known for constructing a sparser $G_{\epsilon}$. Our algorithm is Monte-Carlo, i.e. it produces the correct output with high probability, as are all efficient graph sparsification algorithms.


Empowered by Wireless Communication: Self-Organizing Traffic Collectives

Abstract: In recent years, tremendous progress has been made in understanding the dynamics of vehicle traffic flow and traffic congestion by interpreting traffic as a multi-particle system. This helps to explain the onset and persistence of many undesired phenomena, e.g., traffic jams. It also reflects the apparent helplessness of drivers in traffic, who feel like passive particles that are pushed around by exterior forces; one of the crucial aspects is the inability to communicate and coordinate with other traffic participants. We present distributed methods for solving these fundamental problems, employing modern wireless, ad-hoc, multi-hop networks. The underlying idea is to use these capabilities as the basis for self-organizing methods for coordinating data collection and processing, recognizing traffic phenomena, and changing their structure by coordinated behavior. The overall objective is a multi-level approach that reaches from protocols for local wireless communication, data dissemination, pattern recognition, over hierarchical structuring and coordinated behavior, all the way to large-scale traffic regulation. In this article we describe three types of results: (i) self-organizing and distributed methods for maintaining and collecting data (using our concept of Hovering Data Clouds); (ii) adaptive data dissemination for traffic information systems; (iii) methods for self-recognition of traffic jams. We conclude by describing higher-level aspects of our work.


Adaptive MAC Protocols Using Memory for Networks with Critical Traffic

Abstract: We consider wireless communication networks where network users are subject to critical events such as emergencies and crises. If a critical event occurs to a user, the user needs to send critical traffic as early as possible. However, most existing medium access control (MAC) protocols are not adequate to meet the urgent need for data transmission by users with critical traffic. In this paper, we devise a class of distributed MAC protocols that achieve coordination using the finite-length memory of users containing their own observations and traffic types. We formulate a protocol design problem and find optimal protocols that solve the problem. We show that the proposed protocols enable a user with critical traffic to transmit its critical traffic without interruption from other users after a short delay while allowing users to share the channel efficiently when there is no critical traffic. Moreover, the proposed protocols require short memory and can be implemented without explicit message passing.


Weighted Soft Decision for Cooperative Sensing in Cognitive Radio Networks

Abstract: Enhancing the current services or deploying new services operating in RF spectrum requires more licensed spectrum which may not be provided by the regulatory bodies because of spectrum scarcity. On the contrary, recent studies suggest that many portions of the licensed spectrum remains unused or underused for significant period of time raising the issue of spectrum access without license in an opportunistic manner. Among all the spectrum accessing techniques, sensing based methods are considered optimal for their simplicity and cost effectiveness. In this paper, we introduce a new cooperative spectrum sensing technique which considers the spatial variation of secondary (unlicensed) users and each user's contribution is weighted by a factor that depends on received power and path loss. Compared to existing techniques, the proposed one increases the sensing ability and spectrum utilization, and offers greater robustness to noise uncertainty. Moreover, this cooperative technique uses very simple energy detector as its building block thereby reduces the cost and operational complexity.


A chaos-based approach for information hiding security

Abstract: This paper introduces a new framework for data hiding security. Contrary to the existing ones, the approach introduced here is not based on probability theory. In this paper, a scheme is considered as secure if its behavior is proven unpredictable. The objective of this study is to enrich the existing notions of data hiding security with a new rigorous and practicable one. This new definition of security is based on the notion of topological chaos. It could be used to reinforce the confidence on a scheme previously proven as secure by other approaches and it could also be used to study some classes of attacks that currently cannot be studied by the existing security approaches. After presenting the theoretical framework of the study, a concrete example is detailed in order to show how our approach can be applied.


Chaotic iterations versus Spread-spectrum: chaos and stego security

Abstract: A new framework for information hiding security, called chaos-security, has been proposed in a previous study. It is based on the evaluation of unpredictability of the scheme, whereas existing notions of security, as stego-security, are more linked to information leaks. It has been proven that spread-spectrum techniques, a well-known stego-secure scheme, are chaos-secure too. In this paper, the links between the two notions of security is deepened and the usability of chaos-security is clarified, by presenting a novel data hiding scheme that is twice stego and chaos-secure. This last scheme has better scores than spread-spectrum when evaluating qualitative and quantitative chaos-security properties. Incidentally, this result shows that the new framework for security tends to improve the ability to compare data hiding scheme.


Key Generation in Wireless Sensor Networks Based on Frequency-selective Channels - Design, Implementation, and Analysis

Abstract: Key management in wireless sensor networks faces several new challenges. The scale, resource limitations, and new threats such as node capture necessitate the use of an on-line key generation by the nodes themselves. However, the cost of such schemes is high since their secrecy is based on computational complexity. Recently, several research contributions justified that the wireless channel itself can be used to generate information-theoretic secure keys. By exchanging sampling messages during movement, a bit string can be derived that is only known to the involved entities. Yet, movement is not the only possibility to generate randomness. The channel response is also strongly dependent on the frequency of the transmitted signal. In our work, we introduce a protocol for key generation based on the frequency-selectivity of channel fading. The practical advantage of this approach is that we do not require node movement. Thus, the frequent case of a sensor network with static motes is supported. Furthermore, the error correction property of the protocol mitigates the effects of measurement errors and other temporal effects, giving rise to an agreement rate of over 97%. We show the applicability of our protocol by implementing it on MICAz motes, and evaluate its robustness and secrecy through experiments and analysis.


YAPA: A generic tool for computing intruder knowledge

Abstract: Reasoning about the knowledge of an attacker is a necessary step in many formal analyses of security protocols. In the framework of the applied pi calculus, as in similar languages based on equational logics, knowledge is typically expressed by two relations: deducibility and static equivalence. Several decision procedures have been proposed for these relations under a variety of equational theories. However, each theory has its particular algorithm, and none has been implemented so far. We provide a generic procedure for deducibility and static equivalence that takes as input any convergent rewrite system. We show that our algorithm covers most of the existing decision procedures for convergent theories. We also provide an efficient implementation, and compare it briefly with the tools ProVerif and KiSs.


Integrating multiple sources to answer questions in Algebraic Topology

Abstract: We present in this paper an evolution of a tool from a user interface for a concrete Computer Algebra system for Algebraic Topology (the Kenzo system), to a front-end allowing the interoperability among different sources for computation and deduction. The architecture allows the system not only to interface several systems, but also to make them cooperate in shared calculations.


Modelling and Implementation of ITWS: An ultimate solution to ITS

Abstract: Casualties due to traffic accidents are increasing day by day. Think of this message being displayed on your computer screen while you were driving "there's a possibility of collision with a car in the next few minutes if you go on driving with this speed and direction". Our research is intended towards developing collision avoidance architecture for the latest Intelligent Transport System. The exchange of safety messages among vehicles and with infrastructure devices poses major challenges. Specially, safety messages have to be adaptively distributed within a certain range of a basically unbounded system. These messages are to be well coordinated and processed via different algorithms. The purpose of the paper is to discuss the ITWS (intelligent transportation warning system), we have discussed the Assisted Global Positioning System(AGPS) system providing additional positioning information at variable conditions. We have also discussed study the Data fusion and kalaman filter in details. The performance of kalman filter and output are discussed. Hardware realization of this model is achieved through software defined radio (SDR).


Towards Hardware implementation of video applications in new telecommunications devices

Abstract: Among the areas, most demanding in terms of calculation is the telecommunication and video applications are now included in several telecommunication devices such as set-top boxes, mobile phones. Embedded videos applications in new generations of telecommunication devices need a processing capacity that can not be achieved by the conventional processor, to work around this problem the use of programmable technology has a lot of interest. First, Field Programmable Gate Arrays (FPGAs) present many performance benefits for real-time image processing applications. The FPGA structure is able to exploit spatial and temporal parallelism. In this paper, we present a new method for implementation of the Color Structure Descriptor (CSD) using the FPGA circuit. In fact the (CSD) provides satisfactory image indexing and retrieval results among all colorbased descriptors in MPEG-7. But the real time implementation of this descriptor is still having problems. In this paper we propose a method for adapting this descriptor for possible implementation under the constraints of the video processing in real time. We have verified the real-time implementation of the (CSD) with an image size of 120*80 pixels.


Software Requirements Specification of the IUfA's UUIS -- a Team 2 COMP5541-W10 Project Approach

Abstract: In the 52-page document, we describe our approach to the Software Requirements Specification of the IUfA's UUIS prototype. This includes the overall system description, functional requirements, non-functional requirements, use cases, the corresponding data dictionary for all entities involved, mock user interface (UI) design, and the overall projected cost estimate. The design specification of UUIS can be found in arXiv:1005.0665.


A New Benchmark For Evaluation Of Graph-Theoretic Algorithms

Abstract: We propose a new graph-theoretic benchmark in this paper. The benchmark is developed to address shortcomings of an existing widely-used graph benchmark. We thoroughly studied a large number of traditional and contemporary graph algorithms reported in the literature to have clear understanding of their algorithmic and run-time characteristics. Based on this study, we designed a suite of kernels, each of which represents a specific class of graph algorithms. The kernels are designed to capture the typical run-time behavior of target algorithms accurately, while limiting computational and spatial overhead to ensure its computation finishes in reasonable time. We expect that the developed benchmark will serve as a much needed tool for evaluating different architectures and programming models to run graph algorithms.


On Estimating the First Frequency Moment of Data Streams

Abstract: Estimating the first moment of a data stream defined as $F_1 = \sum_{i \in \{1, 2, \ldots, n\}} \abs{f_i}$ to within $1 \pm \epsilon$-relative error with high probability is a basic and influential problem in data stream processing. A tight space bound of $O(\epsilon^{-2} \log (mM))$ is known from the work of [Kane-Nelson-Woodruff-SODA10]. However, all known algorithms for this problem require per-update stream processing time of $\Omega(\epsilon^{-2})$, with the only exception being the algorithm of [Ganguly-Cormode-RANDOM07] that requires per-update processing time of $O(\log^2(mM)(\log n))$ albeit with sub-optimal space $O(\epsilon^{-3}\log^2(mM))$. In this paper, we present an algorithm for estimating $F_1$ that achieves near-optimality in both space and update processing time. The space requirement is $O(\epsilon^{-2}(\log n + (\log \epsilon^{-1})\log(mM)))$ and the per-update processing time is $O( (\log n)\log (\epsilon^{-1}))$.


TSDS: high-performance merge, subset, and filter software for time series-like data

Abstract: Time Series Data Server (TSDS) is a software package for implementing a server that provides fast super-setting, sub-setting, filtering, and uniform gridding of time series-like data. TSDS was developed to respond quickly to requests for long time spans of data. Data may be served from a fast database, typically created by aggregating granules (e.g., data files) from a remote data source and storing them in a local cache that is optimized for serving time series. The system was designed specifically for time series data, and is optimized for requests where the longest dimension of the requested data structure is time. Scalar, vector, and spectrogram time series types are supported. The user can interact with the server by requesting a time series, a date range, and an optional filter to apply to the data. Available filters include strides, block average/minimum/maximum, exclude, and inequality. Constraint expressions are supported, which allow such operations as a request for data from one time series when a different time series satisfied a specified relationship. TSDS builds upon DAP (Data Access Protocol), NcML (netCDF Mark-up language) and related software libraries. In this work, we describe the current design of this server, as well as planned features and potential implementation strategies.


Generic design of Chinese remaindering schemes

Abstract: We propose a generic design for Chinese remainder algorithms. A Chinese remainder computation consists in reconstructing an integer value from its residues modulo non coprime integers. We also propose an efficient linear data structure, a radix ladder, for the intermediate storage and computations. Our design is structured into three main modules: a black box residue computation in charge of computing each residue; a Chinese remaindering controller in charge of launching the computation and of the termination decision; an integer builder in charge of the reconstruction computation. We then show that this design enables many different forms of Chinese remaindering (e.g. deterministic, early terminated, distributed, etc.), easy comparisons between these forms and e.g. user-transparent parallelism at different parallel grains.


An affine-intuitionistic system of types and effects: confluence and termination

Abstract: We present an affine-intuitionistic system of types and effects which can be regarded as an extension of Barber-Plotkin Dual Intuitionistic Linear Logic to multi-threaded programs with effects. In the system, dynamically generated values such as references or channels are abstracted into a finite set of regions. We introduce a discipline of region usage that entails the confluence (and hence determinacy) of the typable programs. Further, we show that a discipline of region stratification guarantees termination.


Comparing Repository Types - Challenges and barriers for subject-based repositories, research repositories, national repository systems and institutional repositories in serving scholarly communication

Abstract: After two decades of repository development, some conclusions may be drawn as to which type of repository and what kind of service best supports digital scholarly communication, and thus the production of new knowledge. Four types of publication repository may be distinguished, namely the subject-based repository, research repository, national repository system and institutional repository. Two important shifts in the role of repositories may be noted. With regard to content, a well-defined and high quality corpus is essential. This implies that repository services are likely to be most successful when constructed with the user and reader uppermost in mind. With regard to service, high value to specific scholarly communities is essential. This implies that repositories are likely to be most useful to scholars when they offer dedicated services supporting the production of new knowledge. Along these lines, challenges and barriers to repository development may be identified in three key dimensions: a) identification and deposit of content; b) access and use of services; and c) preservation of content and sustainability of service. An indicative comparison of challenges and barriers in some major world regions such as Europe, North America and East Asia plus Australia is offered in conclusion.


Software Design Document, Testing, Deployment and Configuration Management of the IUfA's UUIS -- a Team 3 COMP5541-W10 Project Approach

Abstract: The purpose of this document is to provide technical specifications concerned to the Design of the University Unified Inventory System - Web Portal, of the UIfA. The Team of Developers used a Feedback Waterfall approach to build up the system, under an Object Oriented paradigm. The architectural model followed was the Model-View-Controller, mixed with a Mapper layer between the database and the Model. Some of the patterns utilized in the developing of the System were the Observer Pattern, the Command Pattern, and the Mapper Pattern.


Randomized hybrid linear modeling by local best-fit flats

Abstract: The hybrid linear modeling problem is to identify a set of d-dimensional affine sets in a D-dimensional Euclidean space. It arises, for example, in object tracking and structure from motion. The hybrid linear model can be considered as the second simplest (behind linear) manifold model of data. In this paper we will present a very simple geometric method for hybrid linear modeling based on selecting a set of local best fit flats that minimize a global l1 error measure. The size of the local neighborhoods is determined automatically by the Jones' l2 beta numbers; it is proven under certain geometric conditions that good local neighborhoods exist and are found by our method. We also demonstrate how to use this algorithm for fast determination of the number of affine subspaces. We give extensive experimental evidence demonstrating the state of the art accuracy and speed of the algorithm on synthetic and real hybrid linear data.


Structural Solutions For Additively Coupled Sum Constrained Games

Abstract: We propose and analyze a broad family of games played by resource-constrained players, which are characterized by the following central features: 1) each user has a multi-dimensional action space, subject to a single sum resource constraint; 2) each user's utility in a particular dimension depends on an additive coupling between the user's action in the same dimension and the actions of the other users; and 3) each user's total utility is the sum of the utilities obtained in each dimension. Familiar examples of such multi-user environments in communication systems include power control over frequency-selective Gaussian interference channels and flow control in Jackson networks. In settings where users cannot exchange messages in real-time, we study how users can adjust their actions based on their local observations. We derive sufficient conditions under which a unique Nash equilibrium exists and the best-response algorithm converges globally and linearly to the Nash equilibrium. In settings where users can exchange messages in real-time, we focus on user choices that optimize the overall utility. We provide the convergence conditions of two distributed action update mechanisms, gradient play and Jacobi update.


A two-step fusion process for multi-criteria decision applied to natural hazards in mountains

Abstract: Mountain river torrents and snow avalanches generate human and material damages with dramatic consequences. Knowledge about natural phenomenona is often lacking and expertise is required for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches. Expertise is considered as a decision process based on imperfect information coming from more or less reliable and conflicting sources. A methodology mixing the Analytic Hierarchy Process (AHP), a multi-criteria aid-decision method, and information fusion using Belief Function Theory is described. Fuzzy Sets and Possibilities theories allow to transform quantitative and qualitative criteria into a common frame of discernment for decision in Dempster-Shafer Theory (DST ) and Dezert-Smarandache Theory (DSmT) contexts. Main issues consist in basic belief assignments elicitation, conflict identification and management, fusion rule choices, results validation but also in specific needs to make a difference between importance and reliability and uncertainty in the fusion process.


The Complex Gaussian Kernel LMS algorithm

Abstract: Although the real reproducing kernels are used in an increasing number of machine learning problems, complex kernels have not, yet, been used, in spite of their potential interest in applications such as communications. In this work, we focus our attention on the complex gaussian kernel and its possible application in the complex Kernel LMS algorithm. In order to derive the gradients needed to develop the complex kernel LMS (CKLMS), we employ the powerful tool of Wirtinger's Calculus, which has recently attracted much attention in the signal processing community. Writinger's calculus simplifies computations and offers an elegant tool for treating complex signals. To this end, the notion of Writinger's calculus is extended to include complex RKHSs. Experiments verify that the CKLMS offers significant performance improvements over the traditional complex LMS or Widely Linear complex LMS (WL-LMS) algorithms, when dealing with nonlinearities.


Extension of Wirtinger Calculus in RKH Spaces and the Complex Kernel LMS

Abstract: Over the last decade, kernel methods for nonlinear processing have successfully been used in the machine learning community. However, so far, the emphasis has been on batch techniques. It is only recently, that online adaptive techniques have been considered in the context of signal processing tasks. To the best of our knowledge, no kernel-based strategy has been developed, so far, that is able to deal with complex valued signals. In this paper, we take advantage of a technique called complexification of real RKHSs to attack this problem. In order to derive gradients and subgradients of operators that need to be defined on the associated complex RKHSs, we employ the powerful tool ofWirtinger's Calculus, which has recently attracted much attention in the signal processing community. Writinger's calculus simplifies computations and offers an elegant tool for treating complex signals. To this end, in this paper, the notion of Writinger's calculus is extended, for the first time, to include complex RKHSs and use it to derive the Complex Kernel Least-Mean-Square (CKLMS) algorithm. Experiments verify that the CKLMS can be used to derive nonlinear stable algorithms, which offer significant performance improvements over the traditional complex LMS orWidely Linear complex LMS (WL-LMS) algorithms, when dealing with nonlinearities.


Buffer Management Algorithm Design and Implementation Based on Network Processors

Abstract: To solve the parameter sensitive issue of the traditional RED (random early detection) algorithm, an adaptive buffer management algorithm called PAFD (packet adaptive fair dropping) is proposed. This algorithm supports DiffServ (differentiated services) model of QoS (quality of service). In this algorithm, both of fairness and throughput are considered. The smooth buffer occupancy rate function is adopted to adjust the parameters. By implementing buffer management and packet scheduling on Intel IXP2400, the viability of QoS mechanisms on NPs (network processors) is verified. The simulation shows that the PAFD smoothes the flow curve, and achieves better balance between fairness and network throughput. It also demonstrates that this algorithm meets the requirements of fast data packet processing, and the hardware resource utilization of NPs is higher.


Multistage Hybrid Arabic/Indian Numeral OCR System

Abstract: The use of OCR in postal services is not yet universal and there are still many countries that process mail sorting manually. Automated Arabic/Indian numeral Optical Character Recognition (OCR) systems for Postal services are being used in some countries, but still there are errors during the mail sorting process, thus causing a reduction in efficiency. The need to investigate fast and efficient recognition algorithms/systems is important so as to correctly read the postal codes from mail addresses and to eliminate any errors during the mail sorting stage. The objective of this study is to recognize printed numerical postal codes from mail addresses. The proposed system is a multistage hybrid system which consists of three different feature extraction methods, i.e., binary, zoning, and fuzzy features, and three different classifiers, i.e., Hamming Nets, Euclidean Distance, and Fuzzy Neural Network Classifiers. The proposed system, systematically compares the performance of each of these methods, and ensures that the numerals are recognized correctly. Comprehensive results provide a very high recognition rate, outperforming the other known developed methods in literature.


A Kinetic Triangulation Scheme for Moving Points in The Plane

Abstract: We present a simple randomized scheme for triangulating a set $P$ of $n$ points in the plane, and construct a kinetic data structure which maintains the triangulation as the points of $P$ move continuously along piecewise algebraic trajectories of constant description complexity. Our triangulation scheme experiences an expected number of $O(n^2\beta_{s+2}(n)\log^2n)$ discrete changes, and handles them in a manner that satisfies all the standard requirements from a kinetic data structure: compactness, efficiency, locality and responsiveness. Here $s$ is the maximum number of times where any specific triple of points of $P$ can become collinear, $\beta_{s+2}(q)=\lambda_{s+2}(q)/q$, and $\lambda_{s+2}(q)$ is the maximum length of Davenport-Schinzel sequences of order $s+2$ on $n$ symbols. Thus, compared to the previous solution of Agarwal et al.~\cite{AWY}, we achieve a (slightly) improved bound on the number of discrete changes in the triangulation. In addition, we believe that our scheme is simpler to implement and analyze.


On Building a Knowledge Base for Stability Theory

Abstract: A lot of mathematical knowledge has been formalized and stored in repositories by now: different mathematical theorems and theories have been taken into consideration and included in mathematical repositories. Applications more distant from pure mathematics, however --- though based on these theories --- often need more detailed knowledge about the underlying theories. In this paper we present an example Mizar formalization from the area of electrical engineering focusing on stability theory which is based on complex analysis. We discuss what kind of special knowledge is necessary here and which amount of this knowledge is included in existing repositories.


Attribute Weighting with Adaptive NBTree for Reducing False Positives in Intrusion Detection

Abstract: In this paper, we introduce new learning algorithms for reducing false positives in intrusion detection. It is based on decision tree-based attribute weighting with adaptive na\"ive Bayesian tree, which not only reduce the false positives (FP) at acceptable level, but also scale up the detection rates (DR) for different types of network intrusions. Due to the tremendous growth of network-based services, intrusion detection has emerged as an important technique for network security. Recently data mining algorithms are applied on network-based traffic data and host-based program behaviors to detect intrusions or misuse patterns, but there exist some issues in current intrusion detection algorithms such as unbalanced detection rates, large numbers of false positives, and redundant attributes that will lead to the complexity of detection model and degradation of detection accuracy. The purpose of this study is to identify important input attributes for building an intrusion detection system (IDS) that is computationally efficient and effective. Experimental results performed using the KDD99 benchmark network intrusion detection dataset indicate that the proposed approach can significantly reduce the number and percentage of false positives and scale up the balance detection rates for different types of network intrusions.


Improving Overhead Computation and pre-processing Time for Grid Scheduling System

Abstract: Computational Grid is enormous environments with heterogeneous resources and stable infrastructures among other Internet-based computing systems. However, the managing of resources in such systems has its special problems. Scheduler systems need to get last information about participant nodes from information centers for the purpose of firmly job scheduling. In this paper, we focus on online updating resource information centers with processed and provided data based on the assumed hierarchical model. A hybrid knowledge extraction method has been used to classifying grid nodes based on prediction of jobs' features. An affirmative point of this research is that scheduler systems don't waste extra time for getting up-to-date information of grid nodes. The experimental result shows the advantages of our approach compared to other conservative methods, especially due to its ability to predict the behavior of nodes based on comprehensive data tables on each node.


The New Embedded System Design Methodology For Improving Design Process Performance

Abstract: Time-to-market pressure and productivity gap force vendors and researchers to improve embedded system design methodology. Current used design method, Register Transfer Level (RTL), is no longer be adequate to comply with embedded system design necessity. It needs a new methodology for facing the lack of RTL. In this paper, a new methodology of hardware embedded system modeling process is designed for improving design process performance using Transaction Level Modeling (TLM). TLM is a higher abstraction design concept model above RTL model. Parameters measured include design process time and accuracy of design. For implementing RTL model used Avalon and Wishbone buses, both are System on Chip bus. Performance improvement measured by comparing TLM and RTL model process. The experiment results show performance improvements for Avalon RTL using new design methodology are 1,03 for 3-tiers, 1,47 for 4-tiers and 1,69 for 5-tiers. Performance improvements for Wishbone RTL are 1,12 for 3-tiers, 1,17 for 4-tiers and 1,34 for 5-tiers. These results show the trend of design process improvement.


Semi-Trusted Mixer Based Privacy Preserving Distributed Data Mining for Resource Constrained Devices

Abstract: In this paper a homomorphic privacy preserving association rule mining algorithm is proposed which can be deployed in resource constrained devices (RCD). Privacy preserved exchange of counts of itemsets among distributed mining sites is a vital part in association rule mining process. Existing cryptography based privacy preserving solutions consume lot of computation due to complex mathematical equations involved. Therefore less computation involved privacy solutions are extremely necessary to deploy mining applications in RCD. In this algorithm, a semi-trusted mixer is used to unify the counts of itemsets encrypted by all mining sites without revealing individual values. The proposed algorithm is built on with a well known communication efficient association rule mining algorithm named count distribution (CD). Security proofs along with performance analysis and comparison show the well acceptability and effectiveness of the proposed algorithm. Efficient and straightforward privacy model and satisfactory performance of the protocol promote itself among one of the initiatives in deploying data mining application in RCD.


Adaptive Slot Allocation And Bandwidth Sharing For Prioritized Handoff Calls In Mobile Netwoks

Abstract: Mobility management and bandwidth management are two major research issues in a cellular mobile network. Mobility management consists of two basic components: location management and handoff management. To Provide QoS to the users Handoff is a key element in wireless cellular networks. It is often initiated either by crossing a cell boundary or by deterioration in the quality of signal in the current channel. In this paper, a new admission control policy for cellular mobile network is being proposed. Two important QoS parameter in cellular networks are Call Dropping Probability (CDP) and Handoff Dropping Probability (HDP). CDP represents the probability that a call is dropped due to a handoff failure. HDP represents the probability of a handoff failure due to insufficient available resources in the target cell. Most of the algorithms try to limit the HDP to some target maximum but not CDP. In this paper, we show that when HDP is controlled, the CDP is also controlled to a minimum extent while maintaining lower blocking rates for new calls in the system.


An Efficient Vein Pattern-based Recognition System

Abstract: This paper presents an efficient human recognition system based on vein pattern from the palma dorsa. A new absorption based technique has been proposed to collect good quality images with the help of a low cost camera and light source. The system automatically detects the region of interest from the image and does the necessary preprocessing to extract features. A Euclidean Distance based matching technique has been used for making the decision. It has been tested on a data set of 1750 image samples collected from 341 individuals. The accuracy of the verification system is found to be 99.26% with false rejection rate (FRR) of 0.03%.


On Duplication in Mathematical Repositories

Abstract: Building a repository of proof-checked mathematical knowledge is without any doubt a lot of work, and besides the actual formalization process there also is the task of maintaining the repository. Thus it seems obvious to keep a repsoitory as small as possible, in particular each piece of mathematical knowledge should be formalized only once. In this paper, however, we claim that it might be reasonable or even necessary to duplicate knowledge in a mathematical repository. We analyze different situations and reasons for doing so and provide a number of examples supporting our thesis.


Effective Bandwidth Utilization in IEEE802.11 for VOIP

Abstract: Voice over Internet protocol (VoIP) is one of the most important applications for the IEEE 802.11 wireless local area networks (WLANs). For network planners who are deploying VoIP over WLANs, one of the important issues is the VoIP capacity. VoIP bandwidth consumption over a WAN is one of the most important factors to consider when building a VoIP infrastructure. Failure to account for VoIP bandwidth requirements will severely limit the reliability of a VoIP system and place a huge burden on the WAN infrastructure. Less bandwidth utilization is the key reasons for reduced number of channel accesses in VOIP. But in the QoS point of view the free bandwidth of atleast 1-5% will improve the voice quality. This proposal utilizes the maximum bandwidth by leaving 1-5% free bandwidth. A Bandwidth Data rate Moderation (BDM) algorithm has been proposed which correlates the data rate specified in IEEE802.11b with the free bandwidth. At each time BDM will calculate the bandwidth utilization before sending the packet to improve performance and voice quality of VoIP. The bandwidth calculation in BDM can be done by using Erlang and VOIP bandwidth calculator. Finally, ns2 experimental study shows the relationship between bandwidth utilization, free bandwidth and data rate. The paper concludes that marginal VoIP call rate has been increased by BDM algorithm.


Implementation of the Six Channel Redundancy to achieve fault tolerance in testing of satellites

Abstract: This paper aims to implement the six channel redundancy to achieve fault tolerance in testing of satellites with acoustic spectrum. We mainly focus here on achieving fault tolerance. An immediate application is the microphone data acquisition and to do analysis at the Acoustic Test Facility (ATF) centre, National Aerospace Laboratories. It has an 1100 cubic meter reverberation chamber in which a maximum sound pressure level of 157 dB is generated. The six channel Redundancy software with fault tolerant operation is devised and developed. The data are applied to program written in C language. The program is run using the Code Composer Studio by accepting the inputs. This is tested with the TMS 320C 6727 DSP, Pro Audio Development Kit (PADK).


Performance Oriented Query Processing In GEO Based Location Search Engines

Abstract: Geographic location search engines allow users to constrain and order search results in an intuitive manner by focusing a query on a particular geographic region. Geographic search technology, also called location search, has recently received significant interest from major search engine companies. Academic research in this area has focused primarily on techniques for extracting geographic knowledge from the web. In this paper, we study the problem of efficient query processing in scalable geographic search engines. Query processing is a major bottleneck in standard web search engines, and the main reason for the thousands of machines used by the major engines. Geographic search engine query processing is different in that it requires a combination of text and spatial data processing techniques. We propose several algorithms for efficient query processing in geographic search engines, integrate them into an existing web search query processor, and evaluate them on large sets of real data and query traces.


Tunable Multifunction Filter Using Current Conveyor

Abstract: The paper presents a current tunable multifunction filter using current conveyor. The proposed circuit can be realized as on chip tunable low pass, high pass, band pass and elliptical notch filter. The circuit employs two current conveyors, one OTA, four resistors and two grounded capacitors, ideal for integration. It has only one output terminal and the number of input terminals may be used. Further, there is no requirement for component matching in the circuit. The resonance frequency ({\omega}0) and bandwidth ({\omega}0 /Q) enjoy orthogonal tuning. The cutoff frequency of the filter is tunable by changing the bias current, which makes it on chip tunable filter. The circuit is realized by using commercially available current conveyor AD844 and OTA LM13700. A HSPICE simulation of circuit is also studied for the verification of theoretical results.


Artificial Neural Network based Diagnostic Model For Causes of Success and Failures

Abstract: In this paper an attempt has been made to identify most important human resource factors and propose a diagnostic model based on the back-propagation and connectionist model approaches of artificial neural network (ANN). The focus of the study is on the mobile -communication industry of India. The ANN based approach is particularly important because conventional approaches (such as algorithmic) to the problem solving have their inherent disadvantages. The algorithmic approach is well-suited to the problems that are well-understood and known solution(s). On the other hand the ANNs have learning by example and processing capabilities similar to that of a human brain. ANN has been followed due to its inherent advantage over conversion algorithmic like approaches and having capabilities, training and human like intuitive decision making capabilities. Therefore, this ANN based approach is likely to help researchers and organizations to reach a better solution to the problem of managing the human resource. The study is particularly important as many studies have been carried in developed countries but there is a shortage of such studies in developing nations like India. Here, a model has been derived using connectionist-ANN approach and improved and verified via back-propagation algorithm. This suggested ANN based model can be used for testing the success and failure human factors in any of the communication Industry. Results have been obtained on the basis of connectionist model, which has been further refined by BPNN to an accuracy of 99.99%. Any company to predict failure due to HR factors can directly deploy this model.


Detecting Security threats in the Router using Computational Intelligence

Abstract: nformation security is an issue of global concern. As the Internet is delivering great convenience and benefits to the modern society, the rapidly increasing connectivity and accessibility to the Internet is also posing a serious threat to security and privacy, to individuals, organizations, and nations alike. Finding effective ways to detect, prevent, and respond to intrusions and hacker attacks of networked computers and information systems. This paper presents a knowledge discovery frame work to detect DoS attacks at the boundary controllers (routers). The idea is to use machine learning approach to discover network features that can depict the state of the network connection. Using important network data (DoS relevant features), we have developed kernel machine based and soft computing detection mechanisms that achieve high detection accuracies. We also present our work of identifying DoS pertinent features and evaluating the applicability of these features in detecting novel DoS attacks. Architecture for detecting DoS attacks at the router is presented. We demonstrate that highly efficient and accurate signature based classifiers can be constructed by using important network features and machine learning techniques to detect DoS attacks at the boundary controllers.


Adaptive Tuning Algorithm for Performance tuning of Database Management System

Abstract: Performance tuning of Database Management Systems(DBMS) is both complex and challenging as it involves identifying and altering several key performance tuning parameters. The quality of tuning and the extent of performance enhancement achieved greatly depends on the skill and experience of the Database Administrator (DBA). As neural networks have the ability to adapt to dynamically changing inputs and also their ability to learn makes them ideal candidates for employing them for tuning purpose. In this paper, a novel tuning algorithm based on neural network estimated tuning parameters is presented. The key performance indicators are proactively monitored and fed as input to the Neural Network and the trained network estimates the suitable size of the buffer cache, shared pool and redo log buffer size. The tuner alters these tuning parameters using the estimated values using a rate change computing algorithm. The preliminary results show that the proposed method is effective in improving the query response time for a variety of workload types. .


A Survey of Mobile WiMAX IEEE 802.16m Standard

Abstract: IEEE 802.16m amends the IEEE 802.16 Wireless MAN-OFDMA specification to provide an advanced air interface for operation in licenced bands. It will meet the cellular layer requirements of IMT-Advanced next generation mobile networks. It will be designed to provide significantly improved performance compared to other high rate broadband cellular network systems. For the next generation mobile networks, it is important to consider increasing peak, sustained data reates, corresponding spectral efficiencies, system capacity and cell coverage as well as decreasing latency and providing QoS while carefully considering overall system complexity. In this paper we provide an overview of the state-of-the-art mobile WiMAX technology and its development. We focus our discussion on Physical Layer, MAC Layer, Schedular,QoS provisioning and mobile WiMAX specification.


Incidences in Three Dimensions and Distinct Distances in the Plane

Abstract: We first describe a reduction from the problem of lower-bounding the number of distinct distances determined by a set $S$ of $s$ points in the plane to an incidence problem between points and a certain class of helices (or parabolas) in three dimensions. We offer conjectures involving the new setup, but are still unable to fully resolve them. Instead, we adapt the recent new algebraic analysis technique of Guth and Katz \cite{GK}, as further developed by Elekes et al. \cite{EKS}, to obtain sharp bounds on the number of incidences between these helices or parabolas and points in $\reals^3$. Applying these bounds, we obtain, among several other results, the upper bound $O(s^3)$ on the number of rotations (rigid motions) which map (at least) three points of $S$ to three other points of $S$. In fact, we show that the number of such rotations which map at least $k\ge 3$ points of $S$ to $k$ other points of $S$ is close to $O(s^3/k^{12/7})$. One of our unresolved conjectures is that this number is $O(s^3/k^2)$, for $k\ge 2$. If true, it would imply the lower bound $\Omega(s/\log s)$ on the number of distinct distances in the plane.


Min-Rank Conjecture for Log-Depth Circuits

Abstract: A completion of an m-by-n matrix A with entries in {0,1,*} is obtained by setting all *-entries to constants 0 or 1. A system of semi-linear equations over GF(2) has the form Mx=f(x), where M is a completion of A and f:{0,1}^n --> {0,1}^m is an operator, the i-th coordinate of which can only depend on variables corresponding to *-entries in the i-th row of A. We conjecture that no such system can have more than 2^{n-c\cdot mr(A)} solutions, where c>0 is an absolute constant and mr(A) is the smallest rank over GF(2) of a completion of A. The conjecture is related to an old problem of proving super-linear lower bounds on the size of log-depth boolean circuits computing linear operators x --> Mx. The conjecture is also a generalization of a classical question about how much larger can non-linear codes be than linear ones. We prove some special cases of the conjecture and establish some structural properties of solution sets.


Round-Trip Voronoi Diagrams and Doubling Density in Geographic Networks

Abstract: The round-trip distance function on a geographic network (such as a road network, flight network, or utility distribution grid) defines the "distance" from a single vertex to a pair of vertices as the minimum length tour visiting all three vertices and ending at the starting vertex. Given a geographic network and a subset of its vertices called "sites" (for example a road network with a list of grocery stores), a two-site round-trip Voronoi diagram labels each vertex in the network with the pair of sites that minimizes the round-trip distance from that vertex. Alternatively, given a geographic network and two sets of sites of different types (for example grocery stores and coffee shops), a two-color round-trip Voronoi diagram labels each vertex with the pair of sites of different types minimizing the round-trip distance. In this paper, we prove several new properties of two-site and two-color round-trip Voronoi diagrams in a geographic network, including a relationship between the "doubling density" of sites and an upper bound on the number of non-empty Voronoi regions. We show how those lemmas can be used in new algorithms asymptotically more efficient than previous known algorithms when the networks have reasonable distribution properties related to doubling density, and we provide experimental data suggesting that road networks with standard point-of-interest sites have these properties.


Revenue Optimal Auction for Single-Minded Buyers

Abstract: We study the problem of characterizing revenue optimal auctions for single-minded buyers. Each buyer is interested only in a specific bundle of items and has a value for the same. Both his bundle and its value are his private information. The bundles that buyers are interested in and their corresponding values are assumed to be realized from known probability distributions independent across the buyers. We identify revenue optimal auctions with a simple structure, if the conditional distribution of any buyer's valuation is nondecreasing, in the hazard rates ordering of probability distributions, as a function of the bundle the buyer is interested in. The revenue optimal auction is given by the solution of a maximum weight independent set problem. We provide a novel graphical construction of the weights and highlight important properties of the resulting auction.


Estimating small moments of data stream in nearly optimal space-time

Abstract: For each $p \in (0,2]$, we present a randomized algorithm that returns an $\epsilon$-approximation of the $p$th frequency moment of a data stream $F_p = \sum_{i = 1}^n \abs{f_i}^p$. The algorithm requires space $O(\epsilon^{-2} \log (mM)(\log n))$ and processes each stream update using time $O((\log n) (\log \epsilon^{-1}))$. It is nearly optimal in terms of space (lower bound $O(\epsilon^{-2} \log (mM))$ as well as time and is the first algorithm with these properties. The technique separates heavy hitters from the remaining items in the stream using an appropriate threshold and estimates the contribution of the heavy hitters and the light elements to $F_p$ separately. A key component is the design of an unbiased estimator for $\abs{f_i}^p$ whose data structure has low update time and low variance.


Efficiency Loss in Revenue Optimal Auctions

Abstract: We study efficiency loss in Bayesian revenue optimal auctions. We quantify this as the worst case ratio of loss in the realized social welfare to the social welfare that can be realized by an efficient auction. Our focus is on auctions with single-parameter buyers and where buyers' valuation sets are finite. For binary valued single-parameter buyers with independent (not necessarily identically distributed) private valuations, we show that the worst case efficiency loss ratio (ELR) is no worse than it is with only one buyer; moreover, it is at most 1/2. Moving beyond the case of binary valuations but restricting to single item auctions, where buyers' private valuations are independent and identically distributed, we obtain bounds on the worst case ELR as a function of number of buyers, cardinality of buyers' valuation set, and ratio of maximum to minimum possible values that buyers can have for the item.


Estimating small frequency moments of data stream: a characteristic function approach

Abstract: A data stream is viewed as a sequence of $M$ updates of the form $(\text{index},i,v)$ to an $n$-dimensional integer frequency vector $f$, where the update changes $f_i$ to $f_i + v$, and $v$ is an integer and assumed to be in $\{-m, ..., m\}$. The $p$th frequency moment $F_p$ is defined as $\sum_{i=1}^n \abs{f_i}^p$. We consider the problem of estimating $F_p$ to within a multiplicative approximation factor of $1\pm \epsilon$, for $p \in [0,2]$. Several estimators have been proposed for this problem, including Indyk's median estimator \cite{indy:focs00}, Li's geometric means estimator \cite{pinglib:2006}, an \Hss-based estimator \cite{gc:random07}. The first two estimators require space $\tilde{O}(\epsilon^{-2})$, where the $\tilde{O}$ notation hides polylogarithmic factors in $\epsilon^{-1}, m, n$ and $M$. Recently, Kane, Nelson and Woodruff in \cite{knw:soda10} present a space-optimal and novel estimator, called the log-cosine estimator. In this paper, we present an elementary analysis of the log-cosine estimator in a stand-alone setting. The analysis in \cite{knw:soda10} is more complicated.


Negative Databases for Biometric Data

Abstract: Negative databases - negative representations of a set of data - have been introduced in 2004 to protect the data they contain. Today, no solution is known to constitute biometric negative databases. This is surprising as biometric applications are very demanding of such protection for privacy reasons. The main difficulty comes from the fact that biometric captures of the same trait give different results and comparisons of the stored reference with the fresh captured biometric data has to take into account this variability. In this paper, we give a first answer to this problem by exhibiting a way to create and exploit biometric negative databases.


The Impact of Topology on Byzantine Containment in Stabilization

Abstract: Self-stabilization is an versatile approach to fault-tolerance since it permits a distributed system to recover from any transient fault that arbitrarily corrupts the contents of all memories in the system. Byzantine tolerance is an attractive feature of distributed system that permits to cope with arbitrary malicious behaviors. We consider the well known problem of constructing a maximum metric tree in this context. Combining these two properties prove difficult: we demonstrate that it is impossible to contain the impact of Byzantine nodes in a self-stabilizing context for maximum metric tree construction (strict stabilization). We propose a weaker containment scheme called topology-aware strict stabilization, and present a protocol for computing maximum metric trees that is optimal for this scheme with respect to impossibility result.


Evaluating Accessible Synchronous CMC Applications

Abstract: This paper proposes a more comprehensive evaluation methodology to measure the usability and user experience qualities of accessible synchronous computer-mediated communication applications. The methodology goes beyond current practices by evaluating how the interaction between a user and a product influences the user experience of those at the other endpoint of the communication channel. A major contribution is given with the proposal of a user test where one of the participants tries to guess whether the other participant has a disability or not. The proposed test is inspired in the Turing Test, and is a consequence of user requirements elicited from a group of individuals with motor and speech disabilities. These ideas are tested and validated with two examples of synchronous communication applications.


Views, Program Transformations, and the Evolutivity Problem in a Functional Language

Abstract: We report on an experience to support multiple views of programs to solve the tyranny of the dominant decomposition in a functional setting. We consider two possible architectures in Haskell for the classical example of the expression problem. We show how the Haskell Refactorer can be used to transform one view into the other, and the other way back. That transformation is automated and we discuss how the Haskell Refactorer has been adapted to be able to support this automated transformation. Finally, we compare our implementation of views with some of the literature.


A Population-centric Approach to the Beauty Contest Game

Abstract: An population-centric analysis for a version of the p-beauty contest game is given for the two-player, finite population, and infinite population cases. Winning strategies are characterized in terms of iterative thinking relative to the population. To win the game one needs to iterate more times than the ambient population, but not too many more times depending on the population size and the value of p.


Statistical Model Checking : An Overview

Abstract: Quantitative properties of stochastic systems are usually specified in logics that allow one to compare the measure of executions satisfying certain temporal properties with thresholds. The model checking problem for stochastic systems with respect to such logics is typically solved by a numerical approach that iteratively computes (or approximates) the exact measure of paths satisfying relevant subformulas; the algorithms themselves depend on the class of systems being analyzed as well as the logic used for specifying the properties. Another approach to solve the model checking problem is to \emph{simulate} the system for finitely many runs, and use \emph{hypothesis testing} to infer whether the samples provide a \emph{statistical} evidence for the satisfaction or violation of the specification. In this short paper, we survey the statistical approach, and outline its main advantages in terms of efficiency, uniformity, and simplicity.


Distribution of Cognitive Load in Web Search

Abstract: The search task and the system both affect the demand on cognitive resources during information search. In some situations, the demands may become too high for a person. This article has a three-fold goal. First, it presents and critiques methods to measure cognitive load. Second, it explores the distribution of load across search task stages. Finally, it seeks to improve our understanding of factors affecting cognitive load levels in information search. To this end, a controlled Web search experiment with forty-eight participants was conducted. Interaction logs were used to segment search tasks semi-automatically into task stages. Cognitive load was assessed using a new variant of the dual-task method. Average cognitive load was found to vary by search task stages. It was significantly higher during query formulation and user description of a relevant document as compared to examining search results and viewing individual documents. Semantic information shown next to the search results lists in one of the studied interfaces was found to decrease mental demands during query formulation and examination of the search results list. These findings demonstrate that changes in dynamic cognitive load can be detected within search tasks. Dynamic assessment of cognitive load is of core interest to information science because it enriches our understanding of cognitive demands imposed on people engaged in the search process by a task and the interactive information retrieval system employed.


RAmM Algorithm(Simplex)

Abstract: The evolution of encryption algorithms have led to the development of very complicated and highly versatile algorithms that sacrifice efficiency for better and harder to decrypt results. But by the application of a genetic schema to the encryption of data, a new structure can be created. Genetic methods and procedures are lethal in the way they handle and manipulate data. The RAmM algorithm uses four genetic operations that have been developed specifically for encryption of data. The operations are Replication, Augmentation, Mutation and Multiplication. The proper application of these methods according to the rules that have been found to be the best for getting optimal and correct results produces a "fingerprint" that is unique to a pair of <data , key>. This means that every single data entry can only be decrypted by using the correct set of key. The application of the RAmM algorithm is in the field of image encryption and restoration. The boundary and the pixel values are separately encrypted to produce a very genuine sequence that is never understood to be an image. The beauty of the procedure is that the entire image can be reproduced without any color loss or loss of pixel quality.


Encoding points on hyperelliptic curves over finite fields in deterministic polynomial time

Abstract: We present families of (hyper)elliptic curve which admit an efficient deterministic encoding function.


Variable elimination for building interpreters

Abstract: In this paper, we build an interpreter by reusing host language functions instead of recoding mechanisms of function application that are already available in the host language (the language which is used to build the interpreter). In order to transform user-defined functions into host language functions we use combinatory logic : lambda-abstractions are transformed into a composition of combinators. We provide a mechanically checked proof that this step is correct for the call-by-value strategy with imperative features.


Classification via Incoherent Subspaces

Abstract: This article presents a new classification framework that can extract individual features per class. The scheme is based on a model of incoherent subspaces, each one associated to one class, and a model on how the elements in a class are represented in this subspace. After the theoretical analysis an alternate projection algorithm to find such a collection is developed. The classification performance and speed of the proposed method is tested on the AR and YaleB databases and compared to that of Fisher's LDA and a recent approach based on on $\ell_1$ minimisation. Finally connections of the presented scheme to already existing work are discussed and possible ways of extensions are pointed out.


How to correctly prune tropical trees

Abstract: We present tropical games, a generalization of combinatorial min-max games based on tropical algebras. Our model breaks the traditional symmetry of rational zero-sum games where players have exactly opposed goals (min vs. max), is more widely applicable than min-max and also supports a form of pruning, despite it being less effective than alpha-beta. Actually, min-max games may be seen as particular cases where both the game and its dual are tropical: when the dual of a tropical game is also tropical, the power of alpha-beta is completely recovered. We formally develop the model and prove that the tropical pruning strategy is correct, then conclude by showing how the problem of approximated parsing can be modeled as a tropical game, profiting from pruning.


Fast Digital Convolutions using Bit-Shifts

Abstract: An exact, one-to-one transform is presented that not only allows digital circular convolutions, but is free from multiplications and quantisation errors for transform lengths of arbitrary powers of two. The transform is analogous to the Discrete Fourier Transform, with the canonical harmonics replaced by a set of cyclic integers computed using only bit-shifts and additions modulo a prime number. The prime number may be selected to occupy contemporary word sizes or to be very large for cryptographic or data hiding applications. The transform is an extension of the Rader Transforms via Carmichael's Theorem. These properties allow for exact convolutions that are impervious to numerical overflow and to utilise Fast Fourier Transform algorithms.


An Agent-based Simulation of the Effectiveness of Creative Leadership

Abstract: This paper investigates the effectiveness of creative versus uncreative leadership using EVOC, an agent-based model of cultural evolution. Each iteration, each agent in the artificial society invents a new action, or imitates a neighbor's action. Only the leader's actions can be imitated by all other agents, referred to as followers. Two measures of creativity were used: (1) invention-to-imitation ratio, iLeader, which measures how often an agent invents, and (2) rate of conceptual change, cLeader, which measures how creative an invention is. High iLeader increased mean fitness of ideas, but only when creativity of followers was low. High iLeader was associated with greater diversity of ideas in the early stage of idea generation only. High cLeader increased mean fitness of ideas in the early stage of idea generation; in the later stage it decreased idea fitness. Reasons for these findings and tentative implications for creative leadership in human society are discussed.


Recognizability of Individual Creative Style Within and Across Domains: Preliminary Studies

Abstract: It is hypothesized that creativity arises from the self-mending capacity of an internal model of the world, or worldview. The uniquely honed worldview of a creative individual results in a distinctive style that is recognizable within and across domains. It is further hypothesized that creativity is domaingeneral in the sense that there exist multiple avenues by which the distinctiveness of one's worldview can be expressed. These hypotheses were tested using art students and creative writing students. Art students guessed significantly above chance both which painting was done by which of five famous artists, and which artwork was done by which of their peers. Similarly, creative writing students guessed significantly above chance both which passage was written by which of five famous writers, and which passage was written by which of their peers. These findings support the hypothesis that creative style is recognizable. Moreover, creative writing students guessed significantly above chance which of their peers produced particular works of art, supporting the hypothesis that creative style is recognizable not just within but across domains.


Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection

Abstract: Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been found helpful in many situations, they may degenerate performance and the resultant generalization ability may be even worse than using the labeled data only. In this paper, we try to reduce the chance of performance degeneration of S3VMs. Our basic idea is that, rather than exploiting all unlabeled data, the unlabeled instances should be selected such that only the ones which are very likely to be helpful are exploited, while some highly risky unlabeled instances are avoided. We propose the S3VM-\emph{us} method by using hierarchical clustering to select the unlabeled instances. Experiments on a broad range of data sets over eighty-eight different settings show that the chance of performance degeneration of S3VM-\emph{us} is much smaller than that of existing S3VMs.


On The Power of Tree Projections: Structural Tractability of Enumerating CSP Solutions

Abstract: The problem of deciding whether CSP instances admit solutions has been deeply studied in the literature, and several structural tractability results have been derived so far. However, constraint satisfaction comes in practice as a computation problem where the focus is either on finding one solution, or on enumerating all solutions, possibly projected to some given set of output variables. The paper investigates the structural tractability of the problem of enumerating (possibly projected) solutions, where tractability means here computable with polynomial delay (WPD), since in general exponentially many solutions may be computed. A general framework based on the notion of tree projection of hypergraphs is considered, which generalizes all known decomposition methods. Tractability results have been obtained both for classes of structures where output variables are part of their specification, and for classes of structures where computability WPD must be ensured for any possible set of output variables. These results are shown to be tight, by exhibiting dichotomies for classes of structures having bounded arity and where the tree decomposition method is considered.


CrystalGPU: Transparent and Efficient Utilization of GPU Power

Abstract: General-purpose computing on graphics processing units (GPGPU) has recently gained considerable attention in various domains such as bioinformatics, databases and distributed computing. GPGPU is based on using the GPU as a co-processor accelerator to offload computationally-intensive tasks from the CPU. This study starts from the observation that a number of GPU features (such as overlapping communication and computation, short lived buffer reuse, and harnessing multi-GPU systems) can be abstracted and reused across different GPGPU applications. This paper describes CrystalGPU, a modular framework that transparently enables applications to exploit a number of GPU optimizations. Our evaluation shows that CrystalGPU enables up to 16x speedup gains on synthetic benchmarks, while introducing negligible latency overhead.


Heuristics in Conflict Resolution

Abstract: Modern solvers for Boolean Satisfiability (SAT) and Answer Set Programming (ASP) are based on sophisticated Boolean constraint solving techniques. In both areas, conflict-driven learning and related techniques constitute key features whose application is enabled by conflict analysis. Although various conflict analysis schemes have been proposed, implemented, and studied both theoretically and practically in the SAT area, the heuristic aspects involved in conflict analysis have not yet received much attention. Assuming a fixed conflict analysis scheme, we address the open question of how to identify "good'' reasons for conflicts, and we investigate several heuristics for conflict analysis in ASP solving. To our knowledge, a systematic study like ours has not yet been performed in the SAT area, thus, it might be beneficial for both the field of ASP as well as the one of SAT solving.


Advanced Radio Resource Management for Multi Antenna Packet Radio Systems

Abstract: In this paper, we propose fairness-oriented packet scheduling (PS) schemes with power-efficient control mechanism for future packet radio systems. In general, the radio resource management functionality plays an important role in new OFDMA based networks. The control of the network resource division among the users is performed by packet scheduling functionality based on maximizing cell coverage and capacity satisfying, and certain quality of service requirements. Moreover, multiantenna transmit-receive schemes provide additional flexibility to packet scheduler functionality. In order to mitigate inter-cell and co-channel interference problems in OFDMA cellular networks soft frequency reuse with different power masks patterns is used. Stemming from the earlier enhanced proportional fair scheduler studies for single-input multiple-output (SIMO) and multiple-input multipleoutput (MIMO) systems, we extend the development of efficient packet scheduling algorithms by adding transmit power considerations in the overall priority metrics calculations and scheduling decisions. Furthermore, we evaluate the proposed scheduling schemes by simulating practical orthogonal frequency division multiple access (OFDMA) based packet radio system in terms of throughput, coverage and fairness distribution among users. As a concrete example, under reduced overall transmit power constraint and unequal power distribution for different sub-bands, we demonstrate that by using the proposed power-aware multi-user scheduling schemes, significant coverage and fairness improvements in the order of 70% and 20%, respectively, can be obtained, at the expense of average throughput loss of only 15%.


A Lightweight and Attack Resistant Authenticated Routing Protocol for Mobile Adhoc Networks

Abstract: In mobile ad hoc networks, by attacking the corresponding routing protocol, an attacker can easily disturb the operations of the network. For ad hoc networks, till now many secured routing protocols have been proposed which contains some disadvantages. Therefore security in ad hoc networks is a controversial area till now. In this paper, we proposed a Lightweight and Attack Resistant Authenticated Routing Protocol (LARARP) for mobile ad hoc networks. For the route discovery attacks in MANET routing protocols, our protocol gives an effective security. It supports the node to drop the invalid packets earlier by detecting the malicious nodes quickly by verifying the digital signatures of all the intermediate nodes. It punishes the misbehaving nodes by decrementing a credit counter and rewards the well behaving nodes by incrementing the credit counter. Thus it prevents uncompromised nodes from attacking the routes with malicious or compromised nodes. It is also used to prevent the denial-of-service (DoS) attacks. The efficiency and effectiveness of LARARP are verified through the detailed simulation studies.


A Wireless Sensor Network Air Pollution Monitoring System

Abstract: Sensor networks are currently an active research area mainly due to the potential of their applications. In this paper we investigate the use of Wireless Sensor Networks (WSN) for air pollution monitoring in Mauritius. With the fast growing industrial activities on the island, the problem of air pollution is becoming a major concern for the health of the population. We proposed an innovative system named Wireless Sensor Network Air Pollution Monitoring System (WAPMS) to monitor air pollution in Mauritius through the use of wireless sensors deployed in huge numbers around the island. The proposed system makes use of an Air Quality Index (AQI) which is presently not available in Mauritius. In order to improve the efficiency of WAPMS, we have designed and implemented a new data aggregation algorithm named Recursive Converging Quartiles (RCQ). The algorithm is used to merge data to eliminate duplicates, filter out invalid readings and summarise them into a simpler form which significantly reduce the amount of data to be transmitted to the sink and thus saving energy. For better power management we used a hierarchical routing protocol in WAPMS and caused the motes to sleep during idle time.


Energy and Link Quality Based Routing for Data Gathering Tree in Wireless Sensor Networks Under TINYOS - 2.X

Abstract: Energy is one of the most important and scarce resources in Wireless Sensor Networks (WSN). WSN nodes work with the embedded operating system called TinyOS, which addresses the constrains of the WSN nodes such as limited processing power, memory, energy, etc and it uses the collection Tree Protocol (CTP) to collect the data from the sensor nodes. It uses either the four-bit link estimation or Link Estimation Exchange Protocol (LEEP) to predict the bi directional quality of the wireless link between the nodes and the next hop candidate is based on the estimated link quality. The residual energy of the node is an important key factor, which plays a vital role in the lifetime of the network and hence this has to taken as one of the metric in the parent selection. In this work, we consider the remaining energy of the node as one of the metric to decide the parent in addition to the link quality metrics. The proposed protocol was compared with CTP protocol in terms of number of packets forwarded by each node and packet reception ratio (PRR) of the network. This work was simulated in TOSSIM simulator and the same was tested in Crossbow IRIS radio test bed. The results show that our algorithm performs better than CTP in terms of load distribution and hence the increased lifetime


Adaptive and Secure Routing Protocol for Emergency Mobile Ad Hoc Networks

Abstract: The nature of Mobile Ad hoc NETworks (MANETs) makes them suitable to be utilized in the context of an extreme emergency for all involved rescue teams. We use the term emergency MANETs (eMANETs) in order to describe next generation IP-based networks, which are deployed in emergency cases such as forest fires and terrorist attacks. The main goal within the realm of eMANETs is to provide emergency workers with intelligent devices such as smart phones and PDAs. This technology allows communication "islets" to be established between the members of the same or different emergency teams (policemen, firemen, paramedics). In this article, we discuss an adaptive and secure routing protocol developed for the purposes of eMANETs. We evaluate the performance of the protocol by comparing it with other widely used routing protocols for MANETs. We finally show that the overhead introduced due to security considerations is affordable to support secure ad-hoc communications among lightweight devices.


Impact of Mobility on the Performance of Multicast Routing Protocols in MANET

Abstract: The advent of ubiquitous computing and the proliferation of portable computing devices have raised the importance of mobile ad-hoc network. A major challenge lies in adapting multicast communication into such environments where mobility and link failures are inevitable. The purpose of this paper is to study impact of mobility models in performance of multicast routing protocols in MANET. In this work, three widely used mobility models such as Random Way Point, Reference Point Group and Manhattan mobility models and three popular multicast routing protocols such as On-Demand Multicast Routing Protocol, Multicast Ad hoc On-demand Distance Vector Routing protocol and Adaptive Demand driven Multicast Routing protocol have been chosen and implemented in NS2. Several experiments have been carried out to study the relative strengths, weakness and applicability of multicast protocols to these mobility models.


A Real Time Optimistic Strategy to achieve Concurrency Control in Mobile Environments Using On-demand Multicasting

Abstract: In mobile database environments, multiple users may access similar data items irrespective of their physical location leading to concurrent access anomalies. As disconnections and mobility are the common characteristics in mobile environment, performing concurrent access to a particular data item leads to inconsistency. Most of the approaches use locking mechanisms to achieve concurrency control. However this leads to increase in blocking and abort rate. In this paper an optimistic concurrency control strategy using on-demand multicasting is proposed for mobile database environments which guarantees consistency and introduces application-specific conflict detection and resolution strategies. The simulation results specify increase in system throughput by reducing the transaction abort rates as compared to the other optimistic strategies proposed in literature.


General Model for Infrastructure Multi-channel Wireless LANs

Abstract: In this paper we develop an integrated model for request mechanism and data transmission in multi-channel wireless local area networks. We calculated the performance parameters for single and multi-channel wireless networks when the channel is noisy. The proposed model is general it can be applied to different wireless networks such as IEEE802.11x, IEEE802.16, CDMA operated networks and Hiperlan\2.


An Efficient and Secure Routing Protocol for Mobile Ad-Hoc Networks

Abstract: Efficiency and simplicity of random algorithms have made them a lucrative alternative for solving complex problems in the domain of communication networks. This paper presents a random algorithm for handling the routing problem in Mobile Ad hoc Networks [MANETS].The performance of most existing routing protocols for MANETS degrades in terms of packet delay and congestion caused as the number of mobile nodes increases beyond a certain level or their speed passes a certain level. As the network becomes more and more dynamic, congestion in network increases due to control packets generated by the routing protocols in the process of route discovery and route maintenance. Most of this congestion is due to flooding mechanism used in protocols like AODV and DSDV for the purpose of route discovery and route maintenance or for route discovery as in the case of DSR protocol. This paper introduces the concept of random routing algorithm that neither maintains a routing table nor floods the entire network as done by various known protocols thereby reducing the load on network in terms of number of control packets in a highly dynamic scenario. This paper calculates the expected run time of the designed random algorithm.


On the Minimization of Handover Decision Instability in Wireless Local Area Networks

Abstract: This paper addresses handover decision instability which impacts negatively on both user perception and network performances. To this aim, a new technique called The HandOver Decision STAbility Technique (HODSTAT) is proposed for horizontal handover in Wireless Local Area Networks (WLAN) based on IEEE 802.11standard. HODSTAT is based on a hysteresis margin analysis that, combined with a utilitybased function, evaluates the need for the handover and determines if the handover is needed or avoided. Indeed, if a Mobile Terminal (MT) only transiently hands over to a better network, the gain from using this new network may be diminished by the handover overhead and short usage duration. The approach that we adopt throughout this article aims at reducing the minimum handover occurrence that leads to the interruption of network connectivity (this is due to the nature of handover in WLAN which is a break before make which causes additional delay and packet loss). To this end, MT rather performs a handover only if the connectivity of the current network is threatened or if the performance of a neighboring network is really better comparing the current one with a hysteresis margin. This hysteresis should make a tradeoff between handover occurrence and the necessity to change the current network of attachment. Our extensive simulation results show that our proposed algorithm outperforms other decision stability approaches for handover decision algorithm.


Bandwidth Modeling and Estimation in Peer to Peer Networks

Abstract: Recent studies have shown that the majority of today's internet traffic is related to Peer to Peer (P2P) traffic. The study of bandwidth in P2P networks is very important. Because it helps us in more efficient capacity planning and QoS provisioning when we would like to design a large scale computer networks. In this paper motivated by the behavior of peers (sources or seeds) that is modeled by Ornstein Uhlenbeck (OU) process, we propose a model for bandwidth in P2P networks. This model is represented with a stochastic integral. We also model the bandwidth when we have multiple downloads or uploads. The autocovariance structure of bandwidth in either case is studied and the statistical parameters such as mean, variance and autocovariance are obtained. We then study the queue length behavior of the bandwidth model. The methods for generating synthetic bandwidth process and estimation of the bandwidth parameters using maximum likehood estimation are presented.


Architecture for Cooperative Prefetching in P2P Video-on- Demand System

Abstract: Most P2P VoD schemes focused on service architectures and overlays optimization without considering segments rarity and the performance of prefetching strategies. As a result, they cannot better support VCRoriented service in heterogeneous environment having clients using free VCR controls. Despite the remarkable popularity in VoD systems, there exist no prior work that studies the performance gap between different prefetching strategies. In this paper, we analyze and understand the performance of different prefetching strategies. Our analytical characterization brings us not only a better understanding of several fundamental tradeoffs in prefetching strategies, but also important insights on the design of P2P VoD system. On the basis of this analysis, we finally proposed a cooperative prefetching strategy called "cooching". In this strategy, the requested segments in VCR interactivities are prefetched into session beforehand using the information collected through gossips. We evaluate our strategy through extensive simulations. The results indicate that the proposed strategy outperforms the existing prefetching mechanisms.


Cross-Layer Resource Allocation Scheme Under Heterogeneous Constraints for Next Generation High Rate WPAN

Abstract: In the next generation wireless networks, the growing demand for new wireless applications is accompanied with high expectations for better quality of service (QoS) fulfillment especially for multimedia applications. Furthermore, the coexistence of future unlicensed users with existing licensed users is becoming a challenging task in the next generation communication systems to overcome the underutilization of the spectrum. A QoS and interference aware resource allocation is thus of special interest in order to respond to the heterogeneous constraints of the next generation networks. In this work, we address the issue of resource allocation under heterogeneous constraints for unlicensed multiband ultra-wideband (UWB) systems in the context of Future Home Networks, i.e. the wireless personal area network (WPAN). The problem is first studied analytically using a heterogeneous constrained optimization problem formulation. After studying the characteristics of the optimal solution, we propose a low-complexity suboptimal algorithm based on a cross-layer approach that combines information provided by the PHY and MAC layers. While the PHY layer is responsible for providing the channel quality of the unlicensed UWB users as well as their interference power that they cause on licensed users, the MAC layer is responsible for classifying the unlicensed users using a two-class based approach that guarantees for multimedia services a high-priority level compared to other services. Combined in an efficient and simple way, the PHY and MAC information present the key elements of the aimed resource allocation. Simulation results demonstrate that the proposed scheme provides a good tradeoff between the QoS satisfaction of the unlicensed applications with hard QoS requirements and the limitation of the interference affecting the licensed users.


Class Based Admission Control by Complete Partitioning -Video on Demand Server

Abstract: In the next generation network (NGN) environment specific consideration is on bandwidth minimization, because this reduces the cost of network. In response to the growing market demand for multimedia traffic transmission, NGN concept has been produced. The next generation network provides multimedia services over high speed networks, which supports DVD quality video on demand. Although it has numerous advantages, more exploration of the large-scale deployment video on demand is still needed. The focus of the research presented in this paper is a class based admission control by the complete partitioning of the video on demand server. In this paper we present analytically and by simulation how the blockage probability of the server significantly affects the on demand video request and the service. We also present how the blockage probability affects the performance of the video on demand server.


On the Use of Cellular Automata in Symmetric Cryptography

Abstract: In this work, pseudorandom sequence generators based on finite fields have been analyzed from the point of view of their cryptographic application. In fact, a class of nonlinear sequence generators has been modelled in terms of linear cellular automata. The algorithm that converts the given generator into a linear model based on automata is very simple and is based on the concatenation of a basic structure. Once the generator has been linearized, a cryptanalytic attack that exploits the weaknesses of such a model has been developed. Linear cellular structures easily model sequence generators with application in stream cipher cryptography.


An Envision of Low Cost Mobile Adhoc Network Test Bed in a Laboratory Environment Emulating an Actual MANET

Abstract: Orchestrating a live field trial of wireless mobile networking involves significant cost and logistical issues relating to mobile platforms, support personnel, network and experiment automation and support equipment. The significant cost and logistics required to execute such a field trial can also be limiting in terms of achieving meaningful test results that exercise a practical number of mobile nodes over a significant set of test conditions within a given time. There is no argument that field trials are an important component of dynamic network testing. A field test of prototype will show whether simulations were on right track or not, but that's a big leap to take; going from the simulator directly to the real thing. In conceiving our work, we envisioned a mobile network emulation system that is low cost, flexible and controllable. This paper describes our wireless MANET test bed under development which emulates an actual MANET. Here, we focuses that, this test bed allows the users to automatically generate arbitrary logically network topologies in order to perform real time operations on adhoc network at a relatively low cost in a laboratory environment without having to physically move the nodes in the adhoc network. Thus, we try to "compress" wireless network so that it fits on a single table.


An Elliptic Curve-based Signcryption Scheme with Forward Secrecy

Abstract: An elliptic curve-based signcryption scheme is introduced in this paper that effectively combines the functionalities of digital signature and encryption, and decreases the computational costs and communication overheads in comparison with the traditional signature-then-encryption schemes. It simultaneously provides the attributes of message confidentiality, authentication, integrity, unforgeability, non-repudiation, public verifiability, and forward secrecy of message confidentiality. Since it is based on elliptic curves and can use any fast and secure symmetric algorithm for encrypting messages, it has great advantages to be used for security establishments in store-and-forward applications and when dealing with resource-constrained devices.


Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes

Abstract: Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions reliably. Large and rich sets of features can cause existing algorithms to overfit because of a limited number of samples. We address this shortcoming using $L_1$ regularization in approximate linear programming. Because the proposed method can automatically select the appropriate richness of features, its performance does not degrade with an increasing number of features. These results rely on new and stronger sampling bounds for regularized approximate linear programs. We also propose a computationally efficient homotopy method. The empirical evaluation of the approach shows that the proposed method performs well on simple MDPs and standard benchmark problems.


The ABC of Digital Business Ecosystems

Abstract: The European Commission has the power to inspire, initiate and sponsor huge transnational projects to an extent impossible for most other entities. These projects can address universal themes and develop well-being models that are valuable across a diversity of societies and economies. It is a universal fact that SMEs in all countries provide a substantial proportion of total employment, and conduct much of a nation's innovative activity. Yet these smaller companies struggle in global markets on a far from level playing field, where large companies have distinct advantages. To redress this imbalance the Commission saw it as a priority to improve the trading capability of the Small and Medium-sized Enterprises (SMEs), and perceived digital platforms as the modern means to this end. They considered that the best operational model for a vibrant Web2.0-based Internet services industry would be by analogy to well-performing biological ecosystems. Open Source Software is adopted in the DBE/OPAALS projects as the best support for sustainability of such complex electronic webs, since it minimises interoperability problems, enables code access for cheaper in-house modification or development of systems, and reduces both capital and operating expenditure.


Cloud Computing: Exploring the scope

Abstract: Cloud computing refers to a paradigm shift to overall IT solutions while raising the accessibility, scalability and effectiveness through its enabling technologies. However, migrated cloud platforms and services cost benefits as well as performances are neither clear nor summarized. Globalization and the recessionary economic times have not only raised the bar of a better IT delivery models but also have given access to technology enabled services via internet. Cloud computing has vast potential in terms of lean Retail methodologies that can minimize the operational cost by using the third party based IT capabilities, as a service. It will not only increase the ROI but will also help in lowering the total cost of ownership. In this paper we have tried to compare the cloud computing cost benefits with the actual premise cost which an organization incurs normally. However, in spite of the cost benefits, many IT professional believe that the latest model i.e. "cloud computing" has risks and security concerns. This report demonstrates how to answer the following questions: (1) Idea behind cloud computing. (2) Monetary cost benefits of using cloud with respect to traditional premise computing. (3) What are the various security issues? We have tried to find out the cost benefit by comparing the Microsoft Azure cloud cost with the prevalent premise cost.


Prediction with Expert Advice under Discounted Loss

Abstract: We study prediction with expert advice in the setting where the losses are accumulated with some discounting---the impact of old losses may gradually vanish. We generalize the Aggregating Algorithm and the Aggregating Algorithm for Regression to this case, propose a suitable new variant of exponential weights algorithm, and prove respective loss bounds.


Information Hiding Using Improper Frame Padding

Abstract: Hiding information in network traffic may lead to leakage of confidential information. In this paper we introduce a new steganographic system: the PadSteg (Padding Steganography). To authors' best knowledge it is the first information hiding solution which represents interprotocol steganography i.e. usage of relation between two or more protocols from the TCP/IP stack to enable secret communication. PadSteg utilizes ARP and TCP protocols together with an Etherleak vulnerability (improper Ethernet frame padding) to facilitate secret communication for hidden groups in LANs (Local Area Networks). Basing on real network traces we confirm that PadSteg is feasible in today's networks and we estimate what steganographic bandwidth is achievable while limiting the chance of disclosure. We also point at possible countermeasures against PadSteg.