Title :
Multi-objective Network Coding Optimization Based on NSGA-II Algorithm
Author :
Kun Hao ; Beibei Wang ; Yongmei Luo
Author_Institution :
Sch. of Comput. & Inf. Eng., Tianjin Inst. of Urban Constr., Tianjin, China
Abstract :
Network coding could effectively improve transmission performance of multicast network, but encoding of node brings the additional calculation cost of node. In order to overcome the overhead brought by network coding, a network coding optimization model under the framework of algebraic network coding is designed in this paper, and the joint optimization for both the link cost and coding cost of network coding are carried out based on this model. In addition, the paper proposes MOONC (Multi-Objective Optimization Problem of Network Coding) based on improved NSGA-II algorithm. Adopting non-dominated sorting mechanism, virtual fitness and elitist strategy, this algorithm could not only improve algorithm efficiency and convergence speed, but also guarantee the population diversity. The simulation for typical network topology shows that this algorithm is effective and feasible.
Keywords :
genetic algorithms; multicast communication; network coding; MOONC; NSGA-II algorithm; algebraic network coding; elitist strategy; encoding; joint optimization; multicast network; multiobjective network coding optimization; multiobjective optimization problem; network coding optimization model; network topology; nondominated sorting genetic algorithm; sorting mechanism; transmission performance improvement; virtual fitness; Algorithm design and analysis; Encoding; Network coding; Optimization; Sociology; Statistics; Vectors; Coding Cost; Link Cost; NSGA-II Algorithm; Network Coding;
Conference_Titel :
Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
Conference_Location :
Liaoning
Print_ISBN :
978-1-4673-4499-9
DOI :
10.1109/ICCECT.2012.21