Service Migration or Task Rerouting: A Two-Timescale Online Resource Optimization for MEC

In this paper, a novel two-timescale resource management framework for mobile edge computing (MEC) is constructed. Unlike existing studies, for providing seamless and cost-efficient MEC services, this work aims to strike the balance between service migration and task rerouting for mobile devices (MDs) whenever handovers occur (i.e., switching access from one edge server to another). Considering the network dynamics (e.g., randomness of MDs’ task generations and time-varying channel conditions) and the asynchronization of different management decisions with different triggers, we formulate an online optimization problem for jointly determining: 1) large-timescale decisions, including which edge server should be selected to access, and whether service migration or task rerouting should be chosen for each MD in each large time frame; and 2) small-time scale decisions, including how computing and communication resources should be allocated among MDs with task offloading requests in each small time slot. Then, we propose an online algorithm based on the improved Lyapunov method, together with an iterative algorithm integrating randomized rounding and Lagrange dual techniques, which solves the problem to asymptotic optimum in terms of the long-term average service delay. Theoretical analyses and simulations evaluate the performance of the proposed solution and show its superiority over counterparts.