Secure Task Offloading in Blockchain-Enabled MEC Networks With Improved PBFT Consensus

Abstract

In this paper, we investigate the secure task offloading and computation resource allocation issues in a consortium blockchain-enabled multi-access edge computing (MEC) system. Specifically, edge servers and a cloud center provides user equipments (UEs) with augmented computing power for task processing, while consortium blockchain can provide trust and secure guarantee to UEs in task offloading. Within the MEC system, we intend to minimize the task processing cost of all UEs by jointly optimizing the binary task offloading decision and the computation resource block allocation. Meanwhile, in the blockchain system, we first enhance the consensus procedure by proposing an improved practical Byzantine fault tolerance (IPBFT) consensus algorithm, and then conduct consensus committee selection, thus to minimize consensus delay and fail ratio. The two systems are jointly optimized, subjecting to the computation power of edge nodes, the node number limitation of IPBFT, the task processing and blockchain consensus delay, etc. To address the problem effectively, we reform it into a Markov decision process (MDP) and use proximal policy optimization (PPO) to dynamically learn the optimal joint solution. Simulation results demonstrate that our proposed algorithm converges fast, and performs well in total reward maximization, and UEs’ cost, consensus delay and fail ratio minimization.