Abstract
Mobile edge computing (MEC) is able to provide cloud computing capabilities at network edges by offloading computation tasks to MEC servers deployed in proximity of edge nodes. Therefore, how to make offloading decision for mobile users has become a critical issue. In this paper, we propose a multi-objective computation offloading algorithm combining multi-objective evolutionary algorithm based on decomposition (MOEA/D) with invasive weed optimisation (IWO) and differential evolution (DE). Considering that IWO is a numerical stochastic optimisation method imitating weeds, behaviour in nature and enjoys great robustness, we further improve its searching abilities. In order to reduce computing time, single-object problems can be clustered into several groups in which only one problem can be optimised by IWO and others are optimised by DE. Experimental results show the competitive performance of our proposed algorithm for computation offloading in MEC environments.
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