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International Review on Computers and Software - July 2008 - Papers

Traffic Aware Data Collection MAC Protocol for Wireless Sensor Networks
A Performance Comparison of Energy Efficient MAC Protocols for Wireless Sensor Networks
Fast Transfer of Packets Through DB Routing Using Ant Colony Optimization
TCP Throughput Optimization Over 802.11 MAC Protocol in Multi-hop Ad-hoc Networks
User-Centric Identity Enabled QoS Policy Management for Next Generation Internet
Arabic Literal Amount Recognition by Genetic Fuzzy K Nearest Neighbor Classifier
Grid Base Classifier for Finding Decision Boundary in Supervised Non-parametric Approach for Multiclass Classifiers
The Development of Baselog System and Some Applications
A User-Centered Approach for Debugging Spreadsheets
Automatic Diagnosis of Particular Diseases Using a Fuzzy-Neural Approach
Affective Expression Recognition in Intelligent E-learning System
Text Steganography Using Ligatures
Generalised Evolutionary Cellular Automata Based-approach for Edge Detection
Verifying Dynamic Properties with Past Temporal Operators in the B Refinement
The Effect of Mean Photon Number to the Output Key Rate in Quantum Key Distribution

International Review on Computers and Software - Papers

Traffic Aware Data Collection MAC Protocol for Wireless Sensor Networks
by M. Vahabi, M. H. F. Ghazvini, M. F. A. Rasid, R. S. A. R. Abdullah

Abstract - In this paper, we propose a new medium access control (MAC) protocol for wireless sensor networks for periodic data collection. The proposed MAC scheme is specifically designed for wireless sensor networks which have periodic traffic with different sampling rates. In our protocol design, sink determines the time schedule for all other nodes in the network. We discuss the design of traffic aware MAC protocol and provide a comparison with the similar MAC protocols through simulation. Under different traffic generation rate, our protocol outperforms the previous one in terms of energy consumption and packet delay. Simulation results show that our protocol demonstrates up to 35% better performance than that of most recent protocol which is proposed for this kind of application, in respect of energy consumption. Comparative analysis and simulation results show that our design considerably gives a good compromise between energy efficiency and packet latency.

Keywords: Wireless Sensor Network, Periodic Data Collection, Sampling Rate, Energy Efficiency, End-to-end Delay.

A Performance Comparison of Energy Efficient MAC Protocols for Wireless Sensor Networks

by T. Ezzedine, M. Miladi, R. Bouallegue

Abstract - With the increasing research in sensor networks in recent years, new application domains such as tactical, environmental and medical have evolved. To match the need of those applications, sensor networks require specific protocol solutions. Researchers, over the recent past, have proposed various communication protocols for sensor networks. Among other layers, MAC (Medium Access Control) poses challenges to provide techniques able to reduce the energy consumption, maximize the throughput and improve latency in addition to arbitrate the access to the shared medium. Some of these goals may be conflicting and may require trade-offs. In this paper, we review IEEE 802.11 which is a contention-based protocol, TDMA (Time Division Multiple Access) as a schedule-based method and SMAC, Adaptive SMAC and ZMAC which are hybrid approaches targeted at high traffic wireless sensor networks. Later on, the performances of these protocols are discussed. Our comparison is conducted from the energy property, the latency and the throughput perspective; then, we explore the introduced trade-offs. Furthermore, we outline the characteristics of the studied protocols and we evaluate the relative merit of each.
Copyright © 2008 Praise Worthy Prize S.r.l. - All rights reserved

Keywords: Energy efficiency, medium access control, trade-off, wireless sensor networks.

Fast Transfer of Packets Through DB Routing Using Ant Colony Optimization
by S. Anuradha, G. Raghuram, K. E. Sreenivasa Murthy, B. Gurunath Reddy

Abstract - Routing in computer network is an essential functionality, which influences both the network management as the quality of services in global networks. The management of the traffic flows has to satisfy requirements for volume of traffic to be transmitted as avoidance of congestions for decreasing the transmission delays. These two requirements in general are contradictory. The optimal traffic management is a key issue for the quality of the information services. This Paper presents Depth wise Breadth wise (DB) algorithm, which provides a path to an incoming packet much faster than existing routing algorithms. This is basically an Artificial Intelligence (AI) Concept, which is useful to get from the source to the destination. Moreover, the proposed algorithm is a combination of Depth First search (DFS) and Breadth First Search (BFS) searching techniques. In this paper, DB Routing has been developed based on a general-purpose metaheuristic named Ant Colony Optimization, which is a framework for building ant-inspired algorithms. DB is applied as the routing algorithm in a simulated packet-switched point-to-point network. It is investigated whether DB is able to obtain an increase in throughput when packets are sent between two distinct nodes. Moreover, it is investigated how prioritizing different heuristics effect the quality of the routing performed. It is concluded that DB behaves differently depending on the relative priority of positive feedback negative feedback and local heuristics. Also it is possible to adjust the parameters to achieve best results by improving in routing time.

Keywords: Ant algorithms, Ant Colony Optimization, Positive feedback, Negative feedback, routing, met heuristics and network model.

TCP Throughput Optimization Over 802.11 MAC Protocol in Multi-hop Ad-hoc Networks
by F. R. Armaghani, S. Khatun, S. S. Jamuar, M. F. A. Rasid

Abstract - The acknowledgment strategy has great potential to increase the TCP throughput when it runs over 802.11 MAC protocol. In particular, TCP acknowledgments carry out an extensive number of medium accesses as they compete in the same route as data packets for media. As the load increases, the well-known hidden terminal effects caused by interference between ACK and data packets in MAC layer can degrade TCP performance dramatically if TCP acknowledges every incoming data packets. In this paper, we propose a TCP-MAC interaction strategy which tries to reduce the number of induced ACKs by monitoring the channel condition. To this end, the total collision probability collected along the path in MAC layer is used to properly set the number of the delayed ACKs in TCP. Based on the measured collision probability, TCP sender dynamically adjusts itself to the channel condition by delaying less ACKs in high traffics and more in low traffic conditions. The simulation results show a reasonable tradeoff between performance under moderate and high traffics.

Keywords: Multi-hop ad-hoc networks, Transport Control Protocol (TCP), Delayed Acknowledgment (DA), 802.11 MAC protocol.

User-Centric Identity Enabled QoS Policy Management for Next Generation Internet

by I. Miloucheva, D. Wagner, C. Niephaus, D. Hetzer

Abstract - Background and architectural considerations for identity enabled user-centric QoS policy management are discussed. Different strategies for usage of identity information for enhanced QoS guarantees of users in Next Generation Internet are described. The specific focus is the user-centric identity driven QoS policy management based on the enhancement of the policy management system developed in the EU IST NETQOS project.
The NETQOS architecture supports the dynamic business level QoS policy specification by different actors (users, service providers and network operators) using ontology interfaces and unified QoS policy repository, as well as automated QoS provisioning including functions for policy configuration, hierarchical policy translation, mapping and adaptation of operational policies, policy monitoring and violation detection. User-centric identity enabled NETQOS policy management supports enhanced business models aimed at dynamic and flexible specification of QoS guarantees by users for their applications considering user profiles, Service Level Agreements (SLAs) and context-aware policy provisioning.

Keywords: user-centric, QoS policy, identity management, SLA, context, ontology, business policy, policy translation, autonomous policy management, identity-enabled policy management, monitoring, adaptation.

Arabic Literal Amount Recognition by Genetic Fuzzy K Nearest Neighbor Classifier

by L. Farah, N. Farah, D. Messadeg

Abstract - Pattern recognition is a very intensive research area nowadays. This paper, deals with offline handwriting Arabic words recognition, using a Genetic fuzzy K nearest neighbor proximity measure. In recent years, a fast K nearest neighbor (K-nn) classifier was used with a good result in term of rate of recognition or for the faster time it took. To improve this classifier a new approach is add with the Genetic fuzzy used to improve conventional methods especially in pattern recognition fields. The aim of this paper is Arabic literal amount recognition using a Genetic fuzzy K-nn (GFK-nn). We introduce briefly the technique for processing handwritten words, which begins with features extraction, then their classification. The purpose of the classifier is to allocate a class to the test word on a basis of a training set. The recognition is introduced in two stages. Firstly to classify the obtained word we use GFK-nn. Secondly we introduce the candidate words to a syntactic analysis, a word is kept if it satisfies the syntax. The proposed system was tested on 1200 images and a 95.70% classification success rate was obtained.

Keywords: Handwritten Word Recognition, Genetic Fuzzy K-nn, Neural Network, Syntactic Analysis.

Grid Base Classifier for Finding Decision Boundary in Supervised Non-parametric Approach for Multiclass Classifiers

by M. R. Mohebpour, B. J. Adznan, M. I. Saripan

Abstract - In this paper we propose a new method named -Grid Base Classifier- which combines the benefits of the two previous methods in order to improve classification tasks. The problem with the current lazy algorithm is that they learn quickly, but classify very slowly. On the other hand eager algorithms classify quickly but learn slowly. In comparison to these algorithms, the proposed algorithm can both learn and classify quickly. The method is developed based on the grid structure, whereby it was done to create a powerful and robust methods for classification. In the current research, this new algorithm is tested and applied to multiclass classification of two or more categories which are important for handling practical classification problems. The results showed that the new method could improve both the efficiency and accuracy of pattern classification.

Keywords: Grid, Decision Boundaries, Pattern Recognition, Supervised, Nonparametric, Multiclass.

The Development of Baselog System and Some Applications

by B. Radulovic, I. Berkovic, P. Hotomski, Z. Kazi

Abstract - In the paper is described Baselog system for the deductive databases as an extension of ATP (Automatic Theorem Proving) resolution system. Flexible binding of the Opened-world concept in ATP system and Closed-world reasoning in Datalog and Prolog has been realized by means of introducing the Cwa–rule and implementing Cwa–controller into ATP system. The system management has been realized on the predicate level depending on the semantic completeness of the database contents. Prolog and Datalog defects related to semantically incomplete bases connected with the negation problem and the Cwa–principle have been eliminated. The predicates, whose base is semantically complete are being treated as in Datalog or Prolog systems, while the predicate, whose base is incomplete, is being treated as in ATP system. The examples, illustrating Baselog system advantages, especially about, are quoted: mathematical induction in deductive systems of logic programming, using remote databases and simbolical execution of Pascal programs.

Keywords: Deductive databases, Baselog system, CWA-principle, Prolog, Datalog.

A User-Centered Approach for Debugging Spreadsheets
by Y. Ayalew

Abstract - Spreadsheet programs, artefacts developed by end-user programmers, are used for a variety of important tasks and decisions. However, as the literature indicates, a significant proportion of spreadsheet programs contain faults. This paper presents an approach for efficiently debugging spreadsheet programs which is based on the interval-based testing methodology. The fault tracing technique proposed uses dataflow infor¬mation and cell marks to identify the most influential faulty cell(s) for a given formula cell containing a propagated fault. To evaluate the methodology proposed, a prototype-tool preserving the look-and-feel spreadsheet develo¬pers are accustomed to has been developed and integrated into Microsoft Excel.

Keywords: spreadsheets, end-user programming, debugging, fault tracing.

Automatic Diagnosis of Particular Diseases Using a Fuzzy-Neural Approach
by S. A. Monadjemi, P. Moallem

Abstract - Automatic diagnosis of diseases always has been of interest as an interdisciplinary study amongst computer and medical science researchers. In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and applied to a MLP neural network. The results of the experiments and also the advantages of using a fuzzy approach were discussed as well. Outcomes suggest the role of effective symptoms selection and the advantages of data fuzzificaton on a neural networks-based automatic medical diagnosis system. Employing ETM diseases as the case study, system eventually gets through the 97.5% of correct detection of abnormal cases.

Keywords: Artificial Neural Networks, Fuzzy Logic, Medical Diagnosis, Symptoms, Fuzzification.

Affective Expression Recognition in Intelligent E-learning System
by M. Neji

Abstract - Affective Computing is a new Artificial Intelligence area that deals with the possibility of making computers able to recognize human emotions in different ways. This paper represents a study about the integration of this new area in the intelligent tutoring system. We argue that socially appropriate affective behaviors would provide a new dimension for collaborative learning systems. The main goal is to analyses learner facial expressions and show how Affective Computing could contribute for this interaction, being part of the complete student tracking (traceability) to monitor student behaviors during learning sessions.

Keywords: Affective Computing, Intelligent tutoring system, Facial expression recognition.

Text Steganography Using Ligatures
by M. Shirali-Shahreza, S. Shirali-Shahreza

Abstract - Sending information secretly and communicating covertly have been of great interest for ages. Steganography is one of the main methods for sending the data secretly. Steganography is the art of hiding data in a cover media such as image or audio. In this paper, a new method is proposed for hiding information in digital Unicode texts. In this method, the data is hidden in the ligatures of the text such as “fl” by using Unicode standard features. This method does not make any apparent changes in the original text and have a perfect perceptual transparency.

Keywords: Information Hiding, Ligature Characters, Perceptual Transparency, Text Steganography, Unicode Standard.

Generalised Evolutionary Cellular Automata Based-approach for Edge Detection
by S. Slatnia, O. Kazar

Abstract - We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA) for extracting edges in a given gray or colour image. This best set of local rules determines the future state of CA in an asynchronous way. The Genetic Algorithm (GA) is applied to search the best CA rules that can realize the best edge detection.

Keywords: Genetic Algorithms, Evolutionary Cellular Automata, Edge Detection.

Verifying Dynamic Properties with Past Temporal Operators in the B Refinement
by L. J. Ben Ayed

Abstract - We are interested in specifying and verifying dynamic properties of reactive systems with the B method extended with propositional linear temporal logic PLTL. It is known that from the purely mathematical viewpoint, it is sufficient to use the future logic because the past logic statements can be reformulated in terms of future logic. However, the introduction of past operators enables the production of more natural formulation of a wide class of dynamic properties. From this viewpoint, it is desirable to be able to verify properties directly formulated in terms of past logic. In this paper, we extend the reformulation technique used to verify dynamic properties with PLTL from the situation when we only use future temporal operators to the situation when we can also use past temporal operators. We show how the past fragment of PLTL, as well as the future fragment is preserved by the B refinement, and we present patterns of reformulation and the corresponding sufficient conditions to verify dynamic properties including past time operators by means of cooperation of theorem proving and model checking.

Keywords: Event B, Past temporal formulae, Refinement, Reformulation, Verification.

The Effect of Mean Photon Number to the Output Key Rate in Quantum Key Distribution
by L. I. A. Ghazali, W. A. W. Adnan, M. Mokhtar, A. F. Abas, M. A. Mahdi, M. I. Saripan

Abstract - Quantum Cryptography guarantees absolute confidentiality for secret key exchanged via an optical fiber. The ability lies in the possibility of distributing the secret key securely in the form of photon. We show that there are different values of optimal mean photon number (μ) based on which assumption is considered for Eve’s technology. For lower optimal μ such as μ=0.1 and μ=0.4, the system is more robust to conservative attacks of Eve. However, the system could not support for higher distilled rate at large optimal μ of 1.

Keywords: Mean Photon Number, Output Key Rate.