Computation Offloading Based on a Distributed Overlay Network Cache-Sharing Mechanism in Multi-Access Edge Computing

Yazhi Liu, Pengfei Zhong, Zhigang Yang (), Wei Li and Siwei Li
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Yazhi Liu: College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China
Pengfei Zhong: College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China
Zhigang Yang: College of Electrical Engineering, North China University of Science and Technology, Tangshan 063210, China
Wei Li: College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China
Siwei Li: College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China

Future Internet, 2024, vol. 16, issue 4, 1-24

Abstract: Multi-access edge computing (MEC) enhances service quality for users and reduces computational overhead by migrating workloads and application data to the network edge. However, current solutions for task offloading and cache replacement in edge scenarios are constrained by factors such as communication bandwidth, wireless network coverage, and limited storage capacity of edge devices, making it challenging to achieve high cache reuse and lower system energy consumption. To address these issues, a framework leveraging cooperative edge servers deployed in wireless access networks across different geographical regions is designed. Specifically, we propose the Distributed Edge Service Caching and Offloading (DESCO) network architecture and design a decentralized resource-sharing algorithm based on consistent hashing, named Cache Chord. Subsequently, based on DESCO and aiming to minimize overall user energy consumption while maintaining user latency constraints, we introduce the real-time computation offloading (RCO) problem and transform RCO into a multi-player static game, prove the existence of Nash equilibrium solutions, and solve it using a multi-dimensional particle swarm optimization algorithm. Finally, simulation results demonstrate that the proposed solution reduces the average energy consumption by over 27% in the DESCO network compared to existing algorithms.

Keywords: multi-access edge computing; computation offloading; consistent hashing; P2P overlay network; multi-dimensional discrete PSO (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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