Research Article
A CWMN Spectrum Allocation Based on Multi-strategy Fusion Glowworm Swarm Optimization Algorithm
@INPROCEEDINGS{10.1007/978-3-319-72998-5_12, author={Zhuhua Hu and Yugui Han and Lu Cao and Yong Bai and Yaochi Zhao}, title={A CWMN Spectrum Allocation Based on Multi-strategy Fusion Glowworm Swarm Optimization Algorithm}, proceedings={Wireless Internet. 9th International Conference, WICON 2016, Haikou, China, December 19-20, 2016, Proceedings}, proceedings_a={WICON}, year={2018}, month={1}, keywords={Cognitive wireless mesh network (CWMN) Spectrum allocation Glowworm swarm optimization (GSO) Multi-strategy fusion}, doi={10.1007/978-3-319-72998-5_12} }- Zhuhua Hu
Yugui Han
Lu Cao
Yong Bai
Yaochi Zhao
Year: 2018
A CWMN Spectrum Allocation Based on Multi-strategy Fusion Glowworm Swarm Optimization Algorithm
WICON
Springer
DOI: 10.1007/978-3-319-72998-5_12
Abstract
In cognitive wireless mesh networks, genetic algorithm based spectrum allocation has the problems of easily falling into local optimum, low accuracy and slow convergence. Aiming at the problems, glowworm swarm optimization is applied into spectrum allocation, and a multi-strategy fusion glowworm swarm optimization algorithm is proposed in this paper, in which step size and fluorescein volatilization factor are dynamically optimized and positions of the glowworms that has fallen into local optimum can be disturbed by Gauss mutation operator. Compared with genetic algorithm and basic glowworm swarm algorithm, the theoretical analysis and simulation results show that the proposed algorithm can avoid falling into local optimum, converge more quickly to the global optimal solution, and obtain higher system bandwidth reward.
