Research Article
Computing Resource Allocation for Hybrid Applications of Blockchain and Mobile Edge Computing
@INPROCEEDINGS{10.1007/978-3-031-54521-4_11, author={Yuqi Fan and Jun Zhang and Xu Ding and Zhifeng Jin and Lei Shi}, title={Computing Resource Allocation for Hybrid Applications of Blockchain and Mobile Edge Computing}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 19th EAI International Conference, CollaborateCom 2023, Corfu Island, Greece, October 4-6, 2023, Proceedings, Part I}, proceedings_a={COLLABORATECOM}, year={2024}, month={2}, keywords={Edge computing Blockchain Computing offloading Resource allocation}, doi={10.1007/978-3-031-54521-4_11} }- Yuqi Fan
Jun Zhang
Xu Ding
Zhifeng Jin
Lei Shi
Year: 2024
Computing Resource Allocation for Hybrid Applications of Blockchain and Mobile Edge Computing
COLLABORATECOM
Springer
DOI: 10.1007/978-3-031-54521-4_11
Abstract
In mobile edge computing (MEC), each user chooses and then offloads the task to an edge server, whereas data security is a concern in MEC due to the lack of trust between users and edge servers. Blockchain is introduced to provide a reliable environment for MEC. In blockchain-based MEC, edge servers are used as the nodes in both MEC and blockchain. After processing the users’ tasks, the edge servers upload the results and other task-related information to the blockchain. The edge servers simultaneously execute two kind of tasks, i.e., the tasks offloaded by the users and the blockchain tasks. Therefore, the user offloading decision affects the processing latency of MEC tasks, and there is a trade-off between the resource allocation for MEC and blockchain tasks. However, most existing studies optimize the resource allocation for blockchain and MEC individually, which leads to the suboptimal performance of blockchain-based MEC. In this paper, we study the problem of user offloading decision and the computing resource allocation of edge servers for MEC and blockchain tasks, with the objective to minimize the total processing delay of MEC and blockchain tasks. We propose an algorithm for joint computing resource allocation for MEC and blockchain (JMB). Theoretical analysis proves that JMB is a 3.16-approximation algorithm. Simulation results show that JMB can effectively reduce the delay in blockchain-based MEC.
