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학술지 Evolutionary Algorithms for Route Selection and Rate Allocation in Multirate Multicast Networks
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Applied Intelligence, v.26 no.3, pp.197-215
06MD2300, u-City 적용 센서네트워크 시스템 개발, 표철식
In multirate multicasting, different users (receivers) in the same multicast group can receive service at different rates, depending on the user requirements and the network congestion level. Compared with unirate multicasting, this provides more flexibility to the users and allows more efficient usage of the network resources. In this paper, we simultaneously address the route selection and rate allocation problem in multirate multicast networks; that is, the problem of constructing multiple multicast trees and simultaneously allocating the rate of receivers for maximizing the sum of utilities over all receivers, subject to link capacity and delay constraints for high-bandwidth delay-sensitive applications in point-to-point communication networks. We propose a genetic algorithm for this problem and elaborate on many of the elements in order to improve solution quality and computational efficiency in applying the proposed methods to the problem. These include the genetic representation, evaluation function, genetic operators, and procedure. Additionally, a new method using an artificial intelligent search technique, called the coevolutionary algorithm, is proposed to achieve better solutions, and methods of selecting environmental individuals and evaluating fitness are developed. The results of extensive computational simulations show that the proposed algorithms provide high-quality solutions and outperform existing approach. © Springer Science+Business Media, LLC 2007.
KSP 제안 키워드
Artificial Intelligent, Coevolutionary algorithm, Computational Efficiency, Congestion level, Delay constraint, Evaluation Function, Evolutionary algorithms(EAs), Genetic Algorithm, Genetic Operators, Genetic Representation, High-quality