%0 Journal Article
%A ZHANG Chengrui
%A KE Peng
%A YIN Mei
%T Improved Artificial Bee Colony Algorithm and Its Application in Edge Computing Offloading
%D 2022
%R 10.3778/j.issn.1002-8331.2109-0155
%J Computer Engineering and Applications
%P 150-161
%V 58
%N 7
%X Mobile edge computing（MEC） reduces computing latency and energy consumption by placing computing power at the edge of the network. An artificial bee colony algorithm based on one-dimensional and multi-dimensional dynamic population（OMABC） strategy is proposed to realize the offloading of computationally intensive and time-sensitive application scenarios. Firstly, establish an edge computing offloading model that includes cloud servers, and construct a cost function with energy consumption as a penalty term to minimize delay. Secondly, the offloading decision of the computing task is transformed into the process of optimizing the cost function of the artificial bee colony algorithm. Finally, the effectiveness of OMABC is verified on the CEC 2017 test function. In the edge computing simulation, it is compared with the local offloading strategy, random offloading strategy, the offloading strategy based on particle swarm optimization（PSO） and the offloading strategy based on artificial bee colony algorithm（ABC）. The results show that the edge computing offloading strategy based on OMABC can effectively reduce the cost function of the MEC system and provide more efficient services.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2109-0155