基于改进的免疫克隆蛙跳算法的多约束QoS路由优化研究

doi:10.11959/j.issn.1000-436x.2020102

Abstract

Abstract:

Aiming at the multi-constraint routing problem,a mathematical model was designed,and an improved immune clonal shuffled frog leaping algorithm (IICSFLA) was proposed,which combined immune operator with traditional SFLA.Under the constraints of bandwidth,delay,packet loss rate,delay jitter and energy cost,total energy cost from the source node to the terminal node was computed.The proposed algorithm was used to find an optimal route with minimum energy cost.In the simulation,the performance of IICSFLA with adaptive genetic algorithm and adaptive ant colony optimization algorithm was compared.Experimental results show that IICSFLA solves the problem of multi-constraints QoS unicast routing optimization.The proposed algorithm avoids local optimum and effectively reduces energy loss of data on the transmission path in comparison with adaptive genetic algorithm and adaptive ant colony optimization algorithm.

Key words: shuffled frog leaping algorithm, QoS optimization, routing optimization, genetic algorithm

CLC Number:

TP212.6

Yi LU,Mengying XU,Jie ZHOU. Multi-constraints QoS routing optimization based on improved immune clonal shuffled frog leaping algorithm[J]. Journal on Communications, 2020, 41(5): 141-149.

Figures/Tables 14

References 21

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个体数量/个	子种群数量	局部迭代次数/次	全局迭代次数/次
12	2	30	100

个体数量/个	交叉率	变异率	全局迭代次数/次
12	0.9	0.05	100

个体数量/个	信息挥发因子ρ	信息启发式因子α	期望启发式因子β	全局迭代次数/次
12	0.95	2	2	100

Multi-constraints QoS routing optimization based on improved immune clonal shuffled frog leaping algorithm

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