Online Service Placement and Request Scheduling in MEC Networks

TL;DR

This paper presents an online algorithm for joint service placement and request scheduling in MEC networks, achieving near-optimal performance through a novel decomposition and rounding approach, validated by theory and simulations.

Contribution

It introduces a new online optimization algorithm combining look-ahead regularization and randomized rounding for MEC service placement and scheduling.

Findings

The algorithm achieves a low competitive ratio.

The approach is validated by theoretical analysis.

Simulation results confirm near-optimal performance.

Abstract

Mobile edge computing (MEC) emerges as a promising solution for servicing delay-sensitive tasks at the edge network. A body of recent literature started to focus on cost-efficient service placement and request scheduling. This work investigates the joint optimization of service placement and request scheduling in a dense MEC network, and develops an efficient online algorithm that achieves close-to-optimal performance. Our online algorithm consists of two basic modules: (1) a regularization with look-ahead approach from competitive online convex optimization, for decomposing the offline relaxed minimization problem into multiple sub-problems, each of which can be efficiently solved in each time slot; (2) a randomized rounding method to transform the fractional solution of offline relaxed problem into integer solution of the original minimization problem, guaranteeing a low competitive ratio. Both theoretical analysis and simulation studies corroborate the efficacy of our proposed online MEC optimization algorithm.