Multiuser Computation Offloading for Long-Term Sequential Tasks in Mobile Edge Computing Environments

Mobile edge computing has shown its potential in serving emerging latency-sensitive mobile applications in ultra-dense 5G networks via offloading computation workloads from the remote cloud data center to the nearby network edge. However, current computation offloading studies in the heterogeneous edge environment face multifaceted challenges: Dependencies among computational tasks, resource competition among multiple users, and diverse long-term objectives. Mobile applications typically consist of several functionalities, and one huge category of the applications can be viewed as a series of sequential tasks. In this study, we first proposed a novel multiuser computation offloading framework for long-term sequential tasks. Then, we presented a comprehensive analysis of the task offloading process in the framework and formally defined the multiuser sequential task offloading problem. Moreover, we decoupled the long-term offloading problem into multiple single time slot offloading problems and proposed a novel adaptive method to solve them. We further showed the substantial performance advantage of our proposed method on the basis of extensive experiments.