BRITE: An Approach to Universal Topology Generation
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Edge sets: an effective evolutionary coding of spanning trees
IEEE Transactions on Evolutionary Computation
A framework for allocating clients to rate-constrained multicast servers
Computer Communications
QoS routing based on genetic algorithm
Computer Communications
Multicast server selection: problems, complexity, and solutions
IEEE Journal on Selected Areas in Communications
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Multicast server replication effectively utilizes the network resources and improves the performance of the clients. Selection of servers in such environments decides the quality of services. In this paper, we provide a frame to select replicated servers with genetic algorithm. A two-level coding scheme is developed to represent a server selection candidate to chromosome efficiently. In the coding process, a method based on Dijkstra’s algorithm and random disturbance is designed that ensures generating a valid multicast tree. We discuss two options of genetic operators, namely crossover and mutation only at the first level code (GA1) or two levels (GA2). GA2 offers higher heritability and locality, but it requires more techniques to guarantee the validity of offspring. Extensive simulations demonstrate that both GA1 and GA2 outperform other heuristics. Particularly, GA2 is superior to GA1 in the complex network.