Multiuser Computation Offloading and Downloading for Edge Computing with Virtualization

TL;DR

This paper investigates joint radio and computation resource allocation in multiuser mobile-edge computing systems, addressing I/O interference effects to optimize throughput and energy efficiency through novel low-complexity algorithms.

Contribution

It introduces a decomposition-based approach for designing offloading algorithms that account for I/O interference, improving robustness and performance in multiuser MEC systems.

Findings

Algorithms achieve near-optimal performance in simulations.

Considering I/O interference enhances system robustness.

Proposed methods effectively balance offloading, downloading, and computation.

Abstract

Mobile-edge computing (MEC) is an emerging technology for enhancing the computational capabilities of mobile devices and reducing their energy consumption via offloading complex computation tasks to the nearby servers. Multiuser MEC at servers is widely realized via parallel computing based on virtualization. Due to finite shared I/O resources, interference between virtual machines (VMs), called I/O interference, degrades the computation performance. In this paper, we study the problem of joint radio-and-computation resource allocation (RCRA) in multiuser MEC systems in the presence of I/O interference. Specifically, offloading scheduling algorithms are designed targeting two system performance metrics: sum offloading throughput maximization and sum mobile energy consumption minimization. Their designs are formulated as non-convex mixed-integer programming problems, which account for latency due to offloading, result downloading and parallel computing. A set of low-complexity algorithms are designed based on a decomposition approach and leveraging classic techniques from combinatorial optimization. The resultant algorithms jointly schedule offloading users, control their offloading sizes, and divide time for communication (offloading and downloading) and computation. They are either optimal or can achieve close-to-optimality as shown by simulation. Comprehensive simulation results demonstrate considering of I/O interference can endow on an offloading controller robustness against the performance-degradation factor.