A Two-Timescale Online Optimization for Balancing Service Migration and Task Rerouting in MEC

In this paper, a novel two-timescale resource management framework for mobile edge computing (MEC) is constructed. 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
$i$
) large-timescale decisions, including access selection and service migration or task rerouting selection for each MD, and ii) small-time scale decisions, including computing and communication resource allocations. Then, we propose a two-timescale low-complexity algorithm based on the improved Lyapunov method, which solves the problem to asymptotic optimum in terms of the long-term system-wide average service delay. Theoretical analyses and simulations evaluate the performance of the proposed solution, and show its superiority over counterparts.