Volume 2, Issue 8, August 2010

Classification of Habitual Activities in Behavior-based Network Detection [ Full-Text ]
Deris Stiawan, Abdul Hanan Abdullah and Mohd. Yazid Idris

This paper presents a new method to detect network traffic threats based on packet classification which is result from the identification of insider’s habitual activities.  We assess the habitual activities by examining regular expression of web applications use by insiders together with the existing server activities log and rules pattern from global update. We capture the packets, analyze the packet and finally, categorize into three main categories whether it is normal, suspicious or malicious.  Our method is able to detect threat with low false alarm rate and provides event list handler to rate the risk for prevention purposes. We apply our method to evaluate system security for help security officer (IT Manager and Administrator) to be aware of status network activities.

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Solving a Congestion Problem of Tasks in a Real-Time System Full-Text ]
M. Blej and M. Azizi

In this paper, we try to avoid the congestion of tasks in a realtime context by applying different techniques (this is an extension of our previous works). Keeping in mind this goal, we study the problem of accumulated tokens, since it is connected to the tasks congestion, in a timed Petri net, modeling thus our system and its interaction with the environment This system consists of a robot, a programmable automaton and a computer. The execution of different tasks must be done with respect to some temporal constraints. This is why we use the temporal Petri nets to model the whole system and also its verification. We describe either textually or graphically the obtained Petri nets and the considered constraints using TINA, an open source tool. The studied problem is a consequence of a wrong functioning. In order to solve it, we attempt three approaches: i- the first one is behavioral-like, it reviews the scheduling of different tasks, it is based on granting priorities to specific transitions in order to fire some transitions before others; ii- While the second one is structural-like, and it introduces some changes over the net structure with respect to the system specification; iii- The third one is purely formal; we used a method of supervised control based upon an event graph. The obtained results show that the problem of accumulated tokens in our models is not deeply related to a scheduling problem, but it is a structural problem. We combine the two former approaches together into a hybrid one and we succeed thus in slowing the token accumulation rate without really stop it; while using the third approach, the problem is fully solved but locally.

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Efficient Contention Window Control with Two-Element Array Full-Text ]
Ali Balador, Ali Movaghar and Sam Jabbehdari

In wireless networks, the sharing channel has limited communication bandwidth. So designing efficient Medium Access Control (MAC) protocol with high performances is a major focus in distributed contention-based MAC protocol research. IEEE 802.11 MAC protocol is the most famous standard in this area. But, this standard has a problem with adopting its backoff range based on channel status. It causes some problems in throughput and fairness in a real situation. In this paper, we propose a simple algorithm that maximizes the throughput and fairness among competing nodes. We have divided nodes into four section of our backoff range. Numerical results show improvement in all performances except end to end delay.

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Fuzzy Self Tuning of PID Controller for Multivariable Process Full-Text ]
P. Sujatha Therese and N. Kesavan Nair

These Many realistic controlled processes in industries are Multi-Input Multi-Output (MIMO), having more than one controlled variable that must be manipulated to achieve the desired performance. Control of nonlinear MIMO process is a difficult task because of the non stationary behavior, substantial coupling of multiple variables and severe disturbances. Ziegler-Nichols tuned PID controller performs well around normal working conditions, but their tolerances to process parameter variations are severely affected. The performance of PID can be further improved by making it self-tuning. This paper explains the design of self tuning for a PID controller. The controller consist two part one is conventional PID controller and other one is  fuzzy logic control (FLC) part, which has self tuning capabilities in set point tracking performance. The proposed method is applied to Heater mixer set up which is a multivariable process. To depict the efficacy of the designed controller, the performance is compared with Ziegler-Nichols tuned PID.

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Survey: Image Encryption Using A5/1 and W7 Full-Text ]
Alireza Jolfaei and Abdolrasoul Mirghadri

In this paper, we survey A5/1 and W7 stream ciphers as methods for protecting the distribution of digital images in an efficient and secure way. So, we performed a series of tests and some comparisons to justify their efficiency for image encryption. These tests included key space analysis, histogram analysis, Randomness Tests, information entropy, encryption quality, correlation analysis, differential analysis, sensitivity analysis and performance analysis. All parts of this study were simulated using MATLAB code. Based on all analysis and experimental results, it can be concluded that, the surveyed ciphers are efficient and Feasible with high potential to be adopted for image encryption.

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Energy-aware Algorithm for Mobile Sensor Networks Using Cellular Automata Full-Text ]
Sepideh Adabi, Mohammad Reza Ahmadi, Ali rezaee and Sahar Adabi

According to the traditional definition of Wireless Sensor Networks (WSNs), static expensive sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a sensor network come equipped with battery and from the point of deployment; this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the lifetime of the network by minimizing the energy is an important challenge in Mobile Wireless Sensor Network. Energy conservation in this kind of network can be accomplished by different approaches. One approach is to combine two methods: First utilizing the low-power stand-by mode supported by the wireless devices and second adjusting the transmission range on each node. In this paper, we presented energy conservation solution based on Cellular Automata (CA).The main objective of this solution is to battery reserve based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes in the network.

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Component Driven Approach to Overcome The Challenges in Software Development Process Full-Text ]
Rupinder Kaur and Jyotsna Sengupta

In software process models, focus is on the activities directly related to development of software, such as requirement analysis, design, coding and testing. As the software process models play a vital role in software development, it really forms the core of the software product. Various software process models are proposed till now but the high failure rate in software development has shown the need of new approach. This paper will present a new approach of software process model, which deals with the various issues like changing requirements, quality, cost and time. This approach also helps in managing each phase more efficiently.

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Effects of Packet Size and Wavelength Numbers on Delay and Link Utilization in WRONs by using OWns                                                                                                                                                                                         Full-Text ]
Asima Nisar

New networking protocols are desired essentially in future Optical Wide Area Network (OWAN) environments to meet increasing demands of communication with low latency and high bandwidth. In this paper, a simulation study based on 100 nodes random topology is conducted to observe packet delay patterns and efficient link utilization for two session traffic sources Exponential and CBR (Constant Bit Rate), with number of wavelengths (16, 32, 48 and 64) while varying packet sizes ranging from 100 to 1000 bytes. By using OWns (Optical WDM network simulator), an optimal packet size is presented for Exponential session traffic as one of the design considerations of new protocol in Wavelength Routed Optical Networks (WRONs) with Wavelength Division Multiplexing (WDM) technology. Simulation results also show that Exponential session traffic performs better as compare to CBR session traffic in terms of average packet delay and link utilization.

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Extreme Learning Machine as Maintainability Prediction model for  Object-Oriented Software Systems                                                                                                                                                                                         Full-Text ]
S. O. Olatunji and Z. Rasheed, K. A. Sattar, A. M. Al-Mana, M. Alshayeb and E. A. El-Sebakhy

As the number of object-oriented software systems increases, it becomes more important for organizations to maintain those systems effectively. However, currently only a small number of maintainability prediction models are available for object oriented systems. In this paper, we develop an extreme learning machine (ELM) maintainability prediction model for object-oriented software systems. The model is based on extreme learning machine algorithm for single-hidden layer feed-forward neural networks (SLFNs) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. The model is constructed using popular object-oriented metric datasets, collected from different object-oriented systems. Prediction accuracy of the model is evaluated and compared with commonly used regression-based models and also with Bayesian network based model which was earlier developed using the same datasets. Empirical results from the simulation show that our ELM based model produces promising results in terms of prediction accuracy measures that are better than most of the other earlier implemented models on the same datasets.

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Face Detection System Based on MLP Neural Network Full-Text ]
Nidal F. Shilbayeh and Gaith A. Al-Qudah

Face detection is the problem of determining whether there are human faces in the image and tries to make a judgment on whether or not that image contains a face. In this paper, we propose a face detector using an efficient architecture based on a Multi-Layer Perceptron (MLP) neural network and Maximal Rejection Classifier (MRC). The proposed approach significantly improves the efficiency and the accuracy of detection in comparison with the traditional neural-network techniques. In order to reduce the total computation cost, we organize the neural network in a pre-stage that is able to reject a majority of non-face patterns in the image backgrounds, thereby significantly improving the overall detection efficiency while maintaining the detection accuracy. An important advantage of the new architecture is that it has a homogeneous structure so that it is suitable for very efficient implementation using programmable devices. Comparisons with other state-of-the-art face detection systems are presented. Our proposed approach achieves one of the best detection accuracies with significantly reduced training and detection cost.

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Adaptive Transmission Power Control based Energy Consumption Analysis in Heterogeneous Sensor Networks                                                                                                                                                             Full-Text ]
R Sudarmani and K R Shankar Kumar

Wireless Sensor Networks (WSNs) are battery-powered ad-hoc networks in which sensor nodes are scattered over a region. These networks have high node density but highly resource-constraint in terms of size, power and bandwidth. Most of the existing sensor networks focus on homogeneous sensor networks, but these networks have poor performance in terms of energy consumption and network life time. So it is required to analyse the Heterogeneous Sensor Network (HSN) model for better performance. In this paper, HSN with adaptive transmission power control (ATPC) of low-end sensors are analysed in terms of energy consumption and network life time and compared with HSN without power control. Simulation results prove that heterogeneous sensor networks with ATPC outperform the heterogeneous sensor networks in terms of energy consumption and network life time.

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Unsupervised Approaches for Detection of Web Users Opinion on Products Full-Text ]
Anil Kumar.K.M, Anil Kumar.P and Suresha

Opinion mining is a recent sub discipline of information retrieval which is not about the topic of a document, but with the opinion it expresses. There are number of research activities that focused on determination of the semantic orientation at the word level, since seed words play an important role as sentiment clues in indicating the sentiment of a sentence or a document. Web users document their opinion in the form of reviews or opinionated texts at different opinionated sites, shopping sites, personal pages etc., to express and share their opinion with other web users. The opinion expressed by web users may be on diverse topics such as politics, sports, products, movies etc. These opinions will be very useful to others such as, leaders of political parties, selection committees of various sports, business analysts and other stake holders of products, directors and producers of movies as well as to the other concerned web users. In this paper, we present an unsupervised sentence and document based approaches for finding opinion of web users from opinionated texts and to classify web user’s opinion into positive or negative. Our approach performs better when subjected to different data sets of nearly four hundred and forty five opinionated texts. The results of our approach are good compared to other published results.

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Real Time Communication over Ethernet using Traffic Smoothing with Neural Networks Full-Text ]
Prasant Kumar Pattnaik, Rajib Mall and Gurashish Singh Brar

This paper provides an improvement over a methodology for providing Real Time Communication over Ethernet without changing the existing hardware. We use Neural Networks to forecast the Ethernet Traffic and use this prediction with adaptive traffic smoothing to give better statistical guaranty for Real Time Data. The Traffic Smoothing module installed at each station, smoothes the non real time traffic enforcing a link rate over the non real time traffic. The prediction for the coming Ethernet utilization obtained from the Neural Networks is used to vary the link rate for each station.

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Dynamic Cluster Distribution Routing Protocol For Wireless Sensor Network Full-Text ]
S. K. Padhi, P. K. Pattnaik and B. Puthal

Grouping sensor nodes into cluster has been popularly used  in order to achieve the network scalability. Every cluster needs a leader, and referred as the cluster-head. Many clustering Schemes for Wireless sensor Networks focus on the   stable clustering techniques for mobile environments. In this paper, we have proposed an extension to Low Energy Adaptive Cluster head  protocol namely Dynamic Cluster Distribution Routing Protocol For Wireless Sensor Network in which cluster heads uses Minimum transmission routing for transmitting to base station . We have shown the correctness & effectiveness of our protocol by mathematical simulation studies.

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Framework to Apply Standards in the Development of e-learning Modules Full-Text ]
Amer Nizar AbuAli and Osman Abou-Rabia

Technical standardization has been widely acknowledged as a new and growing area of interest for social-theoretical and historical research. The field of education, and particularly educational technology and distance education (or “e-learning”), has shown the need to develop e–learning courses. In this paper, we present the standards that should be taken into accounts when developing such courses as well as the advantages of applying such standards.

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Implementation of Shared Memory Sparse Direct Solvers for Three Dimensional Finite Element Codes                                                                                                                                                                                         Full-Text ]
Mandhapati P. Raju and Siddhartha K. Khaitan

Parallel computing can significantly aid in reducing the computational time, especially in solving large three dimensional finite element codes. Using parallel solvers on multi-core processors can be very helpful in this regard. High end desktop PC’s having multi-core processors are now quite standard. This multi-core computing power can be effectively utilized by using shared memory computation, done by either using a shared memory based direct solver (e.g. PARDISO), or a multithreaded BLAS library hooked to a sequential solver. In this paper, the relative performance of four different solvers UMFPACK, MUMPS, HSL, PARDISO is evaluated on a 8 processor 64 bit windows test bed. As a result of the beneficial comparative study, the results reported in this paper can serve as a guideline in choosing an appropriate parallel direct solver for effectively utilizing the multi-core capabilities of a given specific hardware setup.

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Optimization of Landmark preprocessing with Multicore Systems Full-Text ]
R. Kalpana and  P. Thambidurai

Determining a shortest path between two given nodes in a directed graph is a common task which is traditionally solved using Dijkstra’s algorithm. There are many techniques available to speedup the Dijkstra’s algorithm while guaranteeing the optimality of the solution. Almost all of the speedup techniques have a substantial amount of parallelism that can be exploited to decrease its running time. The main focus of the work is to implement landmark technique and to identify the segment of the code in landmark preprocessing which can be parallelized to obtain better speedup. The results are compared and analyzed for better performance improvements.

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