Network routing optimisation and effective multimedia transmission to enhance QoS in communication networks
Kusetoğulları, Hüseyin (2012) Network routing optimisation and effective multimedia transmission to enhance QoS in communication networks. PhD thesis, University of Warwick.Full text not available from this repository.
Official URL: http://webcat.warwick.ac.uk/record=b2568696~S1
With the increased usage of communication services in networks, finding routes for reliable transmission and providing effective multimedia communication have become very challenging problems. This has been a strong motivation to examine and develop methods and techniques to find routing paths efficiently and to provide effective multimedia communication. This thesis is mainly concerned with designing, implementing and adapting intelligent algorithms to solve the computational complexity of network routing problems and testing the performance of intelligent algorithms’ applications. It also introduces hybrid algorithms which are developed by using the similarities of genetic algorithm (GA) and particle swarm optimization (PSO) intelligent systems algorithms. Furthermore, it examines the design of a new encoding/decoding method to offer a solution for the problem of unachievable multimedia information in multimedia multicast networks. The techniques presented and developed within the thesis aim to provide maximum utilization of network resources for handling communication problems. This thesis first proposes GA and PSO implementations which are adapted to solve the single and multi-objective functions in network routing problems. To offer solutions for network routing problems, binary variable-length and priority based encoding methods are used in intelligent algorithms to construct valid paths or potential solutions. The performance of generation operators in GA and PSO is examined and analyzed by solving the various shortest path routing problems and it is shown that the performance of algorithms varies based on the operators selected. Moreover, a hybrid algorithm is developed based on the lack of search capability of intelligent algorithms and implemented to solve the single objective function. The proposed method uses a strategy of sharing information between GA and PSO to achieve significant performance enhancement to solve routing optimization problems. The simulation results demonstrate the efficiency of the hybrid algorithm by optimizing the shortest path routing problem. Furthermore, intelligent algorithms are implemented to solve a multi-objective function which involves more constraints of resources in communication networks. The algorithms are adapted to find the multi-optimal paths to provide effective multimedia communication in lossy networks. The simulation results verify that the implemented algorithms are shown as efficient and accurate methods to solve the multi-objective function and find multi-optimal paths to deliver multimedia packets in lossy networks. Furthermore, the thesis proposes a new encoding/decoding method to maximize throughput in multimedia multicast networks. The proposed method is combined with two most used Multiple Description Coding (MDC) methods. The utilization of the proposed method is discussed by comparing two the MDC methods. Through analyzing the simulation results using these intelligent systems algorithms, it has been shown that feasible solutions can be obtained by optimizing complex network problems. Moreover, the methods proposed and developed, which are hybrid algorithms and the encoding/decoding method also demonstrate their efficiency and effectiveness as compared with other techniques.
|Item Type:||Thesis or Dissertation (PhD)|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software|
|Library of Congress Subject Headings (LCSH):||Routing (Computer network management)|
|Institution:||University of Warwick|
|Theses Department:||School of Engineering|
|Supervisor(s)/Advisor:||Leeson, Mark S., 1963- ; Hines, Evor, 1957-|
|Extent:||xix, 188 leaves : ill., charts|
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