Task Offloading and Service Migration Strategies for User Equipments with Mobility Consideration in Mobile Edge Computing
Yan Ding, Chubo Liu, Kenli Li, Zhuo Tang, Keqin Li · 2019
Recently, a great number of works have focused on task offloading optimization in mobile edge computing (MEC). However, rare works involve user equipment (UE) mobility. When involving mobility in MEC, the problem becomes even harder. Even a slight movement of UE can significantly affect the strategy and overhead of the UE. Usually, the types of UE mobility can be categorized as random mobility, short-term predictable mobility, and fully known mobility, depending on whether the future location of the UE is known. In this paper, we aim to optimize task offloading and service migration for UEs with different mobility considerations. Specifically, we try to find appropriate task offloading and service migration strategies to optimize energy consumption or latency of UEs according to the characteristics of different mobility types. We conduct extensive experiments using the real world data which records the movement trajectory of UEs. Experimental results show that our methods perform better compared to six other common strategies and can further reduce the overhead of UEs by using their mobility characteristics.