Energy-Efficient Blockchain-enabled User-Centric Mobile Edge Computing

TL;DR

This paper proposes an energy-efficient, blockchain-enabled user-centric mobile edge computing system that optimizes resource utilization, reduces delay and energy consumption, and enhances security and reliability through a novel consensus mechanism and joint resource optimization.

Contribution

It introduces a novel blockchain-based resource trading mechanism and an ADMM-based optimization framework for energy-efficient, reliable, user-centric MEC systems.

Findings

Up to 33.96% reduction in total delay.

Up to 48.77% reduction in energy consumption.

Enhanced security and reliability in resource trading.

Abstract

In the traditional mobile edge computing (MEC) system, the availability of MEC services is greatly limited for the edge users of the cell due to serious signal attenuation and inter-cell interference. User-centric MEC (UC-MEC) can be seen as a promising solution to address this issue. In UC-MEC, each user is served by a dedicated access point (AP) cluster enabled with MEC capability instead of a single MEC server, however, at the expense of more energy consumption and greater privacy risks. To achieve efficient and reliable resource utilization with user-centric services, we propose an energy efficient blockchain-enabled UC-MEC system where blockchain operations and resource optimization are jointly performed. Firstly, we design a resource-aware, reliable, replicated, redundant, and fault-tolerant (R-RAFT) consensus mechanism to implement secure and reliable resource trading. Then, an optimization framework based on alternating direction method of multipliers (ADMM) is proposed to minimize the total energy consumed by wireless transmission, consensus and task computing, where APs clustering, computing resource allocation and bandwidth allocation are jointly considered. Simulation results show superiority of the proposed UC-MEC system over reference schemes, at most 33.96% reduction in the total delay and 48.77% reduction in the total energy consumption.