Load balancing algorithm based on multiple linear regression analysis in multi-agent systems Online publication date: Wed, 16-May-2018
by Dong-sheng Liu; Xiao-hong Xiao; Xiao-hui Zeng
International Journal of Computational Science and Engineering (IJCSE), Vol. 16, No. 3, 2018
Abstract: With the increase of agents involved in applications of multi-agent systems (MASs), the problem of load balancing is more and more prominent. This paper proposes a novel load balancing algorithm based on multiple linear regression analysis (LBAMLR). By using parallel computing on all servers and utilising partial information about agents' communication, our algorithm can effectively chose the optimal agents set and the suitable destination servers. The simulation results show our proposed algorithm can shorten the computing time and increase the total performance in MAS.
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