Load Balancing of Double Queues and Utility-Workload Tradeoff in Heterogeneous Mobile Edge Computing

Mobile edge computing (MEC) is a popular service paradigm by which mobile devices can offload their latency-sensitive and computation-intensive workloads to edge servers. The MEC service scheduling problem has been investigated in recent years. However, most MEC service scheduling mechanisms only consider workloads on homogeneous edge servers, causing servers’ queue backlogs to be too large when innumerable user requests arrive concurrently. In this paper, we are the first to propose a double-queue workloads scheduling model innovatively, and formulate a system (including user ends and edge server ends) utility into a scheduling optimization problem. To tackle such an NP scheduling problem, we present a Lyapunov-based decomposition strategy to convert the original problem into three equivalent subproblems. By aggregating three subproblem solving strategies, we propose the Lyapunov-based online matching algorithm for edge service scheduling, named LOMES, to obtain an optimal system utility while guaranteeing the load balancing of mobile devices and heterogeneous edge servers. Simulations further validate that LOMES realizes the load balancing of two queue lengths and a $[O(1/V); O(V)]$ tradeoff between the system’s utility and workloads with a utility-workload tradeoff parameter ${V}$ .