OpenRaiser/Intern-Atlas huggingface dataset:
Constructions from Dots and Lines
Venue: arXiv cs.DS 2010
Year: 2010

A graph is a data structure composed of dots (i.e. vertices) and lines (i.e. edges). The dots and lines of a graph can be organized into intricate arrangements. The ability for a graph to denote objects and their relationships to one another allow for a surprisingly large number of things to be modeled as a graph. From the dependencies that link software packages to the wood beams that provide the framing to a house, most anything has a corresponding graph representation. However, just because it is possible to represent something as a graph does not necessarily mean that its graph representation will be useful. If a modeler can leverage the plethora of tools and algorithms that store and process graphs, then such a mapping is worthwhile. This article explores the world of graphs in computing and exposes situations in which graphical models are beneficial.
Simulation of Computer Network Attacks
Venue: arXiv cs.CR 2010
Year: 2010

In this work we present a prototype for simulating computer network attacks. Our objective is to simulate large networks (thousands of hosts, with applications and vulnerabilities) while remaining realistic from the attacker's point of view. The foundation for the simulator is a model of computer intrusions, based on the analysis of real world attacks. In particular we show how to interpret vulnerabilities and exploits as communication channels. This conceptual model gives a tool to describe the theater of operations, targets, actions and assets involved in multistep network attacks. We conclude with applications of the attack simulator.
Mirrored Language Structure and Innate Logic of the Human Brain as a Computable Model of the Oracle Turing Machine
Venue: arXiv cs.LO 2010
Year: 2010

We wish to present a mirrored language structure (MLS) and four logic rules determined by this structure for the model of a computable Oracle Turing machine. MLS has novel features that are of considerable biological and computational significance. It suggests an algorithm of relation learning and recognition (RLR) that enables the deterministic computers to simulate the mechanism of the Oracle Turing machine, or P = NP in a mathematical term.
Asymptotic Equipartition Properties for simple hierarchical and networked structures
Venue: arXiv cs.IT 2010
Year: 2010

We prove asymptotic equipartition properties for simple hierarchical structures (modelled as multitype Galton-Watson trees) and networked structures (modelled as randomly coloured random graphs). For example, for large $n$, a networked data structure consisting of $n$ units connected by an average number of links of order $n/log n$ can be coded by about $nH$ bits, where $H$ is an explicitly defined entropy. The main technique in our proofs are large deviation principles for suitably defined empirical measures.
Semi-Partitioned Hard Real-Time Scheduling with Restricted Migrations upon Identical Multiprocessor Platforms
Venue: arXiv cs.OS 2010
Year: 2010

Algorithms based on semi-partitioned scheduling have been proposed as a viable alternative between the two extreme ones based on global and partitioned scheduling. In particular, allowing migration to occur only for few tasks which cannot be assigned to any individual processor, while most tasks are assigned to specific processors, considerably reduces the runtime overhead compared to global scheduling on the one hand, and improve both the schedulability and the system utilization factor compared to partitioned scheduling on the other hand. In this paper, we address the preemptive scheduling problem of hard real-time systems composed of sporadic constrained-deadline tasks upon identical multiprocessor platforms. We propose a new algorithm and a scheduling paradigm based on the concept of semi-partitioned scheduling with restricted migrations in which jobs are not allowed to migrate, but two subsequent jobs of a task can be assigned to different processors by following a periodic strategy.
Enhancing the Authentication of Bank Cheque Signatures by Implementing Automated System Using Recurrent Neural Network
Venue: arXiv cs.NI 2010
Year: 2010

The associatie memory feature of the Hopfield type recurrent neural network is used for the pattern storage and pattern authentication.This paper outlines an optimization relaxation approach for signature verification based on the Hopfield neural network (HNN)which is a recurrent network.The standard sample signature of the customer is cross matched with the one supplied on the Cheque.The difference percentage is obtained by calculating the different pixels in both the images.The network topology is built so that each pixel in the difference image is a neuron in the network.Each neuron is categorized by its states,which in turn signifies that if the particular pixel is changed.The network converges to unwavering condition based on the energy function which is derived in experiments.The Hopfield's model allows each node to take on two binary state values (changed/unchanged)for each pixel.The performance of the proposed technique is evaluated by applying it in various binary and gray scale images.This paper contributes in finding an automated scheme for verification of authentic signature on bank Cheques.The derived energy function allows a trade off between the influence of its neighborhood and its own criterion.This device is able to recall as well as complete partially specified inputs.The network is trained via a storage prescription that forces stable states to correspond to (local)minima of a network "energy" function.
Real Time and Energy Efficient Transport Protocol for Wireless Sensor Networks
Venue: arXiv cs.NI 2010
Year: 2010

Reliable transport protocols such as TCP are tuned to perform well in traditional networks where packet losses occur mostly because of congestion. Many applications of wireless sensor networks are useful only when connected to an external network. Previous research on transport layer protocols for sensor networks has focused on designing protocols specifically targeted for sensor networks. The deployment of TCP/IP in sensor networks would, however, enable direct connection between the sensor network and external TCP/IP networks. In this paper we focus on the performance of TCP in the context of wireless sensor networks. TCP is known to exhibit poor performance in wireless environments, both in terms of throughput and energy efficiency. To overcome these problems we introduce a mechanism called TCP Segment Caching .We show by simulation that TCP Segment Caching significantly improves TCP Performance so that TCP can be useful e en in wireless sensor
Customized way of Resource Discovery in a Campus Grid
Venue: arXiv cs.NI 2010
Year: 2010

Campus Grid computing involves heterogeneous resources of an organization working in collaboration to sol e the problems that cannot be addressed by a single resource. However, basic problem for Campus Grid users is how to disco er the best resources required for the particular type of a job. There are various approaches using which Grid Discovery can be performed. This paper pro ides the grid resource discovery solutions for Campus Grid using Globus Toolkit which will enable us to customize the resource information according to the requirements based on the jobs to be run on the Campus Grid and present it in our own format. Here we propose building up our own service on top of globus MDS in order to process the information provided by MDS and use it in our Campus Grid Portal.
Controlling program extraction in Elementary Linear Logic
Venue: arXiv cs.LO 2010
Year: 2010

We present an adaptation, based on program extraction in elementary linear logic, of Krivine & Leivant's system FA_2. This system allows to write higher-order equations in order to specify the computational content of extracted programs. The user can then prove a generic formula, using these equations as axioms, whose proof can be extracted into programs that normalize in elementary time and satisfy the specifications. Finally, we show that every elementary recursive functions can be implemented in this system.
Virtual On-demand Test Lab using Cloud based Architecture
Venue: arXiv cs.OH 2010
Year: 2010

Over a past few decades, VM's or Virtual machines have sort of gained a lot of momentum, especially for large scale enterprises where the need for resource optimization & power save is humongous, without compromising with performance or quality. They are a perfect environment to experiment with new applications/technologies in a completely secure and closed environment. This paper discusses how the VM technology can be leveraged to solve day to day requirement of an odd hundreds or thousands of people, organization-wide, with new computational resources using a cluster of heterogeneous low or high-end machines, independent of underlying OS, thereby maximizing resource utilization. It takes into account both opensource (like VirtualBox) & other proprietary technologies (like VMWare Workstations) available till date to propose a viable solution using cloud computing concept. The ease of scalability to multiple folds for optimizing performance & catering to an even larger set are some of the salient features of this approach. Using the snapshot feature, the state of any VM instance could be saved & served back again on request. Now, this implementation is also served by VMWare ESX server but again it's a costly solution & requires dedicated high-end machines to work with.
Offline Arabic Handwriting Recognition Using Artificial Neural Network
Venue: arXiv cs.CL 2010
Year: 2010

The ambition of a character recognition system is to transform a text document typed on paper into a digital format that can be manipulated by word processor software Unlike other languages, Arabic has unique features, while other language doesn't have, from this language these are seven or eight language such as ordo, jewie and Persian writing, Arabic has twenty eight letters, each of which can be linked in three different ways or separated depending on the case. The difficulty of the Arabic handwriting recognition is that, the accuracy of the character recognition which affects on the accuracy of the word recognition, in additional there is also two or three from for each character, the suggested solution by using artificial neural network can solve the problem and overcome the difficulty of Arabic handwriting recognition.
Effect of Distributed Shield Insertion on Crosstalk in Inductively Coupled VLSI Interconnects
Venue: arXiv cs.OH 2010
Year: 2010

Crosstalk in VLSI interconnects is a major constrain in DSM and UDSM technology. Among various strategies followed for its minimization, shield insertion between Aggressor and Victim is one of the prominent options. This paper analyzes the extent of crosstalk in inductively coupled interconnects and minimizes the same through distributed shield insertion. Comparison is drawn between signal voltage and crosstalk voltage in three different conditions i.e. prior to shield insertion, after shield insertion and after additional ground tap insertion at shield terminal.
Outrepasser les limites des techniques classiques de Prise d'Empreintes grace aux Reseaux de Neurones
Venue: arXiv cs.CR 2010
Year: 2010

We present an application of Artificial Intelligence techniques to the field of Information Security. The problem of remote Operating System (OS) Detection, also called OS Fingerprinting, is a crucial step of the penetration testing process, since the attacker (hacker or security professional) needs to know the OS of the target host in order to choose the exploits that he will use. OS Detection is accomplished by passively sniffing network packets and actively sending test packets to the target host, to study specific variations in the host responses revealing information about its operating system. The first fingerprinting implementations were based on the analysis of differences between TCP/IP stack implementations. The next generation focused the analysis on application layer data such as the DCE RPC endpoint information. Even though more information was analyzed, some variation of the "best fit" algorithm was still used to interpret this new information. Our new approach involves an analysis of the composition of the information collected during the OS identification process to identify key elements and their relations. To implement this approach, we have developed tools using Neural Networks and techniques from the field of Statistics. These tools have been successfully integrated in a commercial software (Core Impact).
Fast Incremental and Personalized PageRank
Venue: arXiv cs.DS 2010
Year: 2010

In this paper, we analyze the efficiency of Monte Carlo methods for incremental computation of PageRank, personalized PageRank, and similar random walk based methods (with focus on SALSA), on large-scale dynamically evolving social networks. We assume that the graph of friendships is stored in distributed shared memory, as is the case for large social networks such as Twitter. For global PageRank, we assume that the social network has $n$ nodes, and $m$ adversarially chosen edges arrive in a random order. We show that with a reset probability of $ε$, the total work needed to maintain an accurate estimate (using the Monte Carlo method) of the PageRank of every node at all times is $O(\frac{n\ln m}{ε^{2}})$. This is significantly better than all known bounds for incremental PageRank. For instance, if we naively recompute the PageRanks as each edge arrives, the simple power iteration method needs $Ω(\frac{m^2}{\ln(1/(1-ε))})$ total time and the Monte Carlo method needs $O(mn/ε)$ total time; both are prohibitively expensive. Furthermore, we also show that we can handle deletions equally efficiently. We then study the computation of the top $k$ personalized PageRanks starting from a seed node, assuming that personalized PageRanks follow a power-law with exponent $α< 1$. We show that if we store $R>q\ln n$ random walks starting from every node for large enough constant $q$ (using the approach outlined for global PageRank), then the expected number of calls made to the distributed social network database is $O(k/(R^{(1-α)/α}))$. We also present experimental results from the social networking site, Twitter, verifying our assumptions and analyses. The overall result is that this algorithm is fast enough for real-time queries over a dynamic social network.
Algebraic Constructions of Graph-Based Nested Codes from Protographs
Venue: arXiv cs.IT 2010
Year: 2010

Nested codes have been employed in a large number of communication applications as a specific case of superposition codes, for example to implement binning schemes in the presence of noise, in joint network-channel coding, or in physical-layer secrecy. Whereas nested lattice codes have been proposed recently for continuous-input channels, in this paper we focus on the construction of nested linear codes for joint channel-network coding problems based on algebraic protograph LDPC codes. In particular, over the past few years several constructions of codes have been proposed that are based on random lifts of suitably chosen base graphs. More recently, an algebraic analog of this approach was introduced using the theory of voltage graphs. In this paper we illustrate how these methods can be used in the construction of nested codes from algebraic lifts of graphs.
Universal Loop-Free Super-Stabilization
Venue: arXiv cs.DC 2010
Year: 2010

We propose an univesal scheme to design loop-free and super-stabilizing protocols for constructing spanning trees optimizing any tree metrics (not only those that are isomorphic to a shortest path tree). Our scheme combines a novel super-stabilizing loop-free BFS with an existing self-stabilizing spanning tree that optimizes a given metric. The composition result preserves the best properties of both worlds: super-stabilization, loop-freedom, and optimization of the original metric without any stabilization time penalty. As case study we apply our composition mechanism to two well known metric-dependent spanning trees: the maximum-flow tree and the minimum degree spanning tree.
The quest for LEDBAT fairness
Venue: arXiv cs.NI 2010
Year: 2010

BitTorrent developers have recently introduced a new application layer congestion control algorithm based on UDP framing at transport layer and currently under definition at the IETF LEDBAT Working Group. LEDBAT is a delay-based protocol which aims at offering a "lower than Best Effort" data transfer service, with a lower priority with respect to elastic TCP and interactive traffic (e.g., VoIP, game). However, in its current specification, LEDBAT is affected by a late-comer advantage: indeed the last flow arriving at the bottleneck is more aggressive due to a wrong estimation of the base delay and finally takes over all resources. In this work, we study several solutions to the late-comer problem by means of packet level simulations and simple analysis: in the investigation process, we individuate the root cause for LEDBAT unfairness and propose effective countermeasures.
Products of Weighted Logic Programs
Venue: arXiv cs.AI 2010
Year: 2010

Weighted logic programming, a generalization of bottom-up logic programming, is a well-suited framework for specifying dynamic programming algorithms. In this setting, proofs correspond to the algorithm's output space, such as a path through a graph or a grammatical derivation, and are given a real-valued score (often interpreted as a probability) that depends on the real weights of the base axioms used in the proof. The desired output is a function over all possible proofs, such as a sum of scores or an optimal score. We describe the PRODUCT transformation, which can merge two weighted logic programs into a new one. The resulting program optimizes a product of proof scores from the original programs, constituting a scoring function known in machine learning as a ``product of experts.'' Through the addition of intuitive constraining side conditions, we show that several important dynamic programming algorithms can be derived by applying PRODUCT to weighted logic programs corresponding to simpler weighted logic programs. In addition, we show how the computation of Kullback-Leibler divergence, an information-theoretic measure, can be interpreted using PRODUCT.
A convenient differential category
Venue: arXiv cs.LO 2010
Year: 2010

In this paper, we show that the category of Mackey-complete, separated, topological convex bornological vector spaces and bornological linear maps is a differential category. Such spaces were introduced by Frölicher and Kriegl, where they were called convenient vector spaces. While much of the structure necessary to demonstrate this observation is already contained in Frölicher and Kriegl's book, we here give a new interpretation of the category of convenient vector spaces as a model of the differential linear logic of Ehrhard and Regnier. Rather than base our proof on the abstract categorical structure presented by Frölicher and Kriegl, we prefer to focus on the bornological structure of convenient vector spaces. We believe bornological structures will ultimately yield a wide variety of models of differential logics.
Fast Self-Stabilizing Minimum Spanning Tree Construction
Venue: arXiv cs.DC 2010
Year: 2010

We present a novel self-stabilizing algorithm for minimum spanning tree (MST) construction. The space complexity of our solution is $O(\log^2n)$ bits and it converges in $O(n^2)$ rounds. Thus, this algorithm improves the convergence time of all previously known self-stabilizing asynchronous MST algorithms by a multiplicative factor $Θ(n)$, to the price of increasing the best known space complexity by a factor $O(\log n)$. The main ingredient used in our algorithm is the design, for the first time in self-stabilizing settings, of a labeling scheme for computing the nearest common ancestor with only $O(\log^2n)$ bits.
Cross Layer Aware Adaptive MAC based on Knowledge Based Reasoning for Cognitive Radio Computer Networks
Venue: arXiv cs.NI 2010
Year: 2010

In this paper we are proposing a new concept in MAC layer protocol design for Cognitive radio by combining information held by physical layer and MAC layer with analytical engine based on knowledge based reasoning approach. In the proposed system a cross layer information regarding signal to interference and noise ratio (SINR) and received power are analyzed with help of knowledge based reasoning system to determine minimum power to transmit and size of contention window, to minimize backoff, collision, save power and drop packets. The performance analysis of the proposed protocol indicates improvement in power saving, lowering backoff and significant decrease in number of drop packets. The simulation environment was implement using OMNET++ discrete simulation tool with Mobilty framework and MiXiM simulation library.
Minimization of Handoff Failure Probability for Next-Generation Wireless Systems
Venue: arXiv cs.NI 2010
Year: 2010

During the past few years, advances in mobile communication theory have enabled the development and deployment of different wireless technologies, complementary to each other. Hence, their integration can realize a unified wireless system that has the best features of the individual networks. Next-Generation Wireless Systems (NGWS) integrate different wireless systems, each of which is optimized for some specific services and coverage area to provide ubiquitous communications to the mobile users. In this paper, we propose to enhance the handoff performance of mobile IP in wireless IP networks by reducing the false handoff probability in the NGWS handoff management protocol. Based on the information of false handoff probability, we analyze its effect on mobile speed and handoff signaling delay.
Porting Decision Tree Algorithms to Multicore using FastFlow
Venue: arXiv cs.DC 2010
Year: 2010

The whole computer hardware industry embraced multicores. For these machines, the extreme optimisation of sequential algorithms is no longer sufficient to squeeze the real machine power, which can be only exploited via thread-level parallelism. Decision tree algorithms exhibit natural concurrency that makes them suitable to be parallelised. This paper presents an approach for easy-yet-efficient porting of an implementation of the C4.5 algorithm on multicores. The parallel porting requires minimal changes to the original sequential code, and it is able to exploit up to 7X speedup on an Intel dual-quad core machine.
Power law in website ratings
Venue: arXiv cs.IR 2010
Year: 2010

In the practical work of websites popularization, analysis of their efficiency and downloading it is of key importance to take into account web-ratings data. The main indicators of website traffic include the number of unique hosts from which the analyzed website was addressed and the number of granted web pages (hits) per unit time (for example, day, month or year). Of certain interest is the ratio between the number of hits (S) and hosts (H). In practice there is even used such a concept as "average number of viewed pages" (S/H), which on default supposes a linear dependence of S on H. What actually happens is that linear dependence is observed only as a partial case of power dependence, and not always. Another new power law has been discovered on the Internet, in particular, on the WWW.
Generating a Family of Byzantine Tolerant Protocol Implementations Using a Meta-Model Architecture
Venue: arXiv cs.DC 2010
Year: 2010

We describe an approach to modelling a Byzantine tolerant distributed algorithm as a family of related finite state machines, generated from a single meta-model. Various artefacts are generated from each state machine, including diagrams and source-level protocol implementations. The approach allows a state machine formulation to be applied to problems for which it would not otherwise be suitable, increasing confidence in correctness.