Computer networks (3rd ed.)
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Genetic Algorithms and the Immune System
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Quality-of-service routing for supporting multimedia applications
IEEE Journal on Selected Areas in Communications
Multicast routing algorithms and protocols: a tutorial
IEEE Network: The Magazine of Global Internetworking
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The current QoS multicast routing model aims to solve a one-objective optimization problem with one or more bounded-constraints, such as delay, delay jitter, bandwidth, etc. To satisfy the individual requirement for users in multiple QoS networks, we analyze the limitation of the current model and propose a new QoS multicast routing model that supports multi-objective optimization. The new model considers the QoS guarantee as QoS optimization objectives rather than QoS constraints. It overcomes the limitations that exist in the traditional multicast routing model. Furthermore, a new routing algorithm to deal with the new model based on immune principles and Pareto concepts is given. In this algorithm, a gene library is introduced to speed up the algorithm to satisfy the real-time requirement of the routing problem. The initial experimental results have shown that the new algorithm can effectively produce more than one Pareto optimization solution compromising all QoS objectives within one single running.