Multipoint communication by hierarchically encoded data
IEEE INFOCOM '92 Proceedings of the eleventh annual joint conference of the IEEE computer and communications societies on One world through communications (Vol. 3)
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
Optimal partition of QoS requirements on unicast paths and multicast trees
IEEE/ACM Transactions on Networking (TON)
Genetic Algorithms Plus Data Structures Equals Evolution Programs
Genetic Algorithms Plus Data Structures Equals Evolution Programs
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Developing IP Multicast Networks
Developing IP Multicast Networks
On Finding Feasible Solutions for the Delay Constrained Group Multicast Routing Problem
IEEE Transactions on Computers
New methods for competitive coevolution
Evolutionary Computation
Forming neural networks through efficient and adaptive coevolution
Evolutionary Computation
Applying adaptive algorithms to epistatic domains
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Research: A group multicast routing algorithm by using multiple minimum Steiner trees
Computer Communications
A framework for routing and congestion control for multicast information flows
IEEE Transactions on Information Theory
Multicast server selection: problems, complexity, and solutions
IEEE Journal on Selected Areas in Communications
A scalable low-overhead rate control algorithm for multirate multicast sessions
IEEE Journal on Selected Areas in Communications
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In this paper, we simultaneously address the route selection and rate allocation problem in multirate multicast networks. We propose the evolutionary computation algorithm based on a genetic algorithm for this problem and elaborate upon 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. The results of extensive computational simulations show that the proposed algorithms provide high quality solutions and outperform existing approach.