An evolutionary game for joint wireless and cloud resource allocation in mobile edge computing

This paper mainly focuses on developing a joint cloud and wireless resource allocation algorithm based on evolutionary game (JRA-EG) considering mobile terminals' energy consumption and time delay as well as monetary cost in mobile edge computing environment. The mobile terminals (MTs) in different service areas form different populations. In addition, the competition among populations of MTs in different service areas is to share the limited amount of bandwidth and computation resources in the accessible service providers (SPs). We analyse the stability property of the evolutionary game model and obtain the evolutionary equilibrium (EE). EE is acquired by replicator dynamics approach. Simulation results show that our JRA-EG algorithm can converge to the EE rapidly. Compared with the existing algorithms, the algorithms can save more energy and have less time delay when input data size becomes larger.