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Analytical Modeling of a Multi-queue Nodes Network Router

International Journal of Automation and computing 2011年第4期8卷 459-464页

作者： Hussein Al-Bahadili Jafar Ababneh fadi thabtah Faculty of Information Technology Petra University Amman Jordan Faculty of Information Technology and Sciences World Islamic Sciences and Education University Amman Jordan Faculty of Information Technology Philadelphia University Amman Jordan

This paper presents the derivation of an analytical model for a multi-queue nodes network router, which is referred to as the multi-queue nodes （mQN） model. In this model, expressions are derived to calculate two performance metrics, namely, the queue node and system utilization factors. In order to demonstrate the flexibility and effectiveness of the mQN model in analyzing the performance of an mQN network router, two scenarios are performed. These scenarios investigated the variation of queue nodes and system utilization factors against queue nodes dropping probability for various system sizes and packets arrival routing probabilities. The performed scenarios demonstrated that the mQN analytical model is more flexible and effective when compared with experimental tests and computer simulations in assessing the performance of an mQN network router.

关键词： Congested networks network routers active queue managements multi-queue nodes (mQN) systems analytical model- ing utilization factor.

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Modeling discrete-time analytical models based on random early detection: Exponential and linear

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International Journal of Modeling, Simulation, and Scientific Computing 2015年第3期6卷 85-106页

作者： Hussein Abdel-Jaber fadi thabtah Mike Woodward Department of Information Technology and Computing Faculty of Computer Studies Arab Open University Kingdom of Saudi Arabia Ebusiness Department Canadian University of DubaiUAE Department of Computing University of Bradford Bradford BD71DPUK

Congestion control is among primary topics in computer network in which random early detection(RED)method is one of its common ***,RED suffers from drawbacks in particular when its“average queue length”is set below the buffer’s“minimum threshold”position which makes the router buffer quickly *** deal with this issue,this paper proposes two discrete-time queue analytical models that aim to utilize an instant queue length parameter as a congestion *** assigns mean queue length(mql)and average queueing delay smaller values than those for RED and eventually reduces buffers overflow.A comparison between RED and the proposed analytical models was conducted to identify the model that offers better *** proposed models outperform the classic RED in regards to mql and average queueing delay measures when congestion *** work also compares one of the proposed models(RED-Linear)with another analytical model named threshold-based linear reduction of arrival rate(TLRAR).The results of the mql,average queueing delay and the probability of packet loss for TLRAR are deteriorated when heavy congestion occurs,whereas,the results of our RED-Linear were not impacted and this shows superiority of our model.

关键词： Analytical modeling congestion control discrete-time queues performance measures simulation

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A dynamic rule-induction method for classification in data mining

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Journal of Management Analytics 2015年第3期2卷 233-253页

作者： Issa Qabajeh fadi thabtah Francisco Chiclana E-Business Department Canadian University of DubaiDubaiUAE Computing and Informatics Department De Montfort UniversityLeicesterUK Centre for Computational Intelligence De Montfort UniversityLeicesterUK

Rule induction(RI)produces classifiers containing simple yet effective‘If–Then’rules for decision *** algorithms normally based on PRISM suffer from a few drawbacks mainly related to rule pruning and rule-sharing items(attribute values)in the training data *** response to the above two issues,a new dynamic rule induction(DRI)method is *** a rule is produced and its related training data instances are discarded,DRI updates the frequency of attribute values that are used to make the next in-line rule to reflect the data ***,the attribute value frequencies are dynamically adjusted each time a rule is generated rather statically as in *** enables DRI to generate near perfect rules and realistic *** results using different University of California Irvine data sets show competitive performance in regards to error rate and classifier size of DRI when compared to other RI algorithms.

关键词： data mining classification rules rule induction expected accuracy

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ANALYTICAL MODELS BASED DISCRETE-TIME QUEUEING FOR THE CONGESTED NETWORK

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International Journal of Modeling, Simulation, and Scientific Computing 2012年第1期3卷 68-89页

作者： MOFLEH AL-DIABAT HUSSEIN ABDEL-JABER fadi thabtah OSMAN ABOU-RABIA MAHMOUD KISHTA Computer Science Department Al-al-Bayt University Jordan Department of Computer Science The World Islamic Sciences&Education(W.I.S.E.)University Amman Jordan Management Information System Department Philadelphia University AmmanJordan Department of Mathematics and Computer Science Laurentian University Sudbury ONCanada Dean of Academic Research Philadelphia University AmmanJordan

Congestion is one of the well-studied problems in computer networks,which occurs when the request for network resources exceeds the buffer *** active queue management techniques such as BLUE and RED have been proposed in the literature to control congestions in early *** this paper,we propose two discrete-time queueing network analytical models to drop the arrival packets in preliminary stages when the network becomes *** first model is based on Lambda Decreasing and it drops packets from a probability value to another higher value according to the buffer *** the second proposed model drops packets linearly based on the current queue *** compare the performance of both our models with the original BLUE in order to decide which of these methods offers better quality of *** comparison is done in terms of packet dropping probability,average queue length,throughput ratio,average queueing delay,and packet loss rate.

关键词： Analytical models congestion control discrete-time queueing simulation

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