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Evolutionary Algorithm Optimization of Edge Delivery Sites in Next Generation Multi-service Content Distribution Networks

Abstract : In the past decade or so we have been experiencing an extraordinary explosion of data volumes first in wireline networks and recently even in mobile wireless networks. Optimizing bandwidth utilization is critical for planning and deploying efficient networks that are capable of delivering new services like IPTV over cost-oriented implementations. Models of distributed content caching in the access network have been employed - for example - as analytical optimization tools in order to tackle associated problems. A modified capacitated quality-of-service network (QoS) model is proposed herein in order to optimize the placement of the sites of surrogate media servers (central offices-COs) on the access part of a content distribution network (CDN). The novelty of the proposed approach lies in the fact that capacitated quality-of-service network optimization is cast as an optimization problem over two rather than one optimization variables-objectives. Implementation cost and link delay as determined by capacity/utilization requirements are the optimization functionals-objectives. Optimization of the network architecture is carried out via a multiobjective evolutionary algorithm that encodes all possible edges between the first level aggregation points of the access network. Proper priorities are assigned to different types of traffic according to class of service. Two main services are considered, namely live broadcast/IPTV and video on demand services (VoD). The media servers/COs are incorporated into the infrastructure of the access nodes in a step-by-step fashion modifying the traffic requirements between source and sink nodes of the optimal configurations of the access network. The evolution of the Pareto front is investigated in each case.
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Ioannis M. Stephanakis, Dimitrios Logothetis. Evolutionary Algorithm Optimization of Edge Delivery Sites in Next Generation Multi-service Content Distribution Networks. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. pp.192-202, ⟨10.1007/978-3-642-23957-1_22⟩. ⟨hal-01571335⟩



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