Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA | Zendy

Yang Liu | Zendy; Jin Qi Zhu | Zendy; Jinao Wang | Zendy

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Computation Offloading Optimization in Mobile Edge Computing Based on HIBSA

Author(s) -

Yang Liu,

Jin Qi Zhu,

Jinao Wang

Publication year - 2021

Publication title -

mobile information systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.346

H-Index - 34

eISSN - 1875-905X

pISSN - 1574-017X

DOI - 10.1155/2021/7716654

Subject(s) - computer science , mobile edge computing , computation offloading , computation , scheduling (production processes) , distributed computing , task (project management) , edge computing , edge device , optimization problem , multi objective optimization , pareto principle , energy consumption , enhanced data rates for gsm evolution , mobile device , hotspot (geology) , mathematical optimization , cloud computing , artificial intelligence , algorithm , operating system , mathematics , machine learning , ecology , management , geophysics , economics , biology , geology

Multiaccess edge computation (MEC) is a hotspot in 5G network. The problem of task offloading is one of the core problems in MEC. In this paper, a novel computation offloading model which partitions tasks into subtasksis proposed. This model takes communication and computing resources, energy consumption of intelligent mobile devices, and weight of tasks into account. We then transform the model into a multiobjective optimization problem based on Pareto that balances the task weight and time efficiency of the offloaded tasks. In addition, an algorithm based on hybrid immune and bat scheduling algorithm (HIBSA) is further designed to tackle the proposed multiobjective optimization problem. The experimental results show that HIBSA can meet the requirements of both the task execution deadline and the weight of the offloaded tasks.

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