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Joint Offloading and Resource Allocation in Cooperative Blockchain-Enabled MEC System

Published: 02 October 2021 Publication History

Abstract

Mobile edge computing (MEC) is regarded as an effective solution for processing computation-intensive tasks. Edge servers with limited resources which are deployed nearby mobile devices (MDs) suffer from many constraints than remote cloud, and relying on a single edge server have significantly reduced system performance. For relieving the mutual distrust and the conflict of interests problem between MDs and edge servers, and providing a data secure transmission MEC system. In this paper, we take MEC system security solved by blockchain technology into consideration, to utilize the cooperative computation offloading which enables edge servers to help each other in computation-intensive tasks. We investigate a long-term MEC system cost (energy consumption and processing delay) minimization problem while ensuring the transactional throughput rate of the blockchain network. Furthermore, we model the optimization problem as an Markov decision process (MDP). We design a dynamic offloading and resource allocation scheme based on Double Deep Q-network algorithm (DDQN). The simulation results show that our proposed algorithm is superior to others and it can improve system performance effectively.

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Cited By

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  • (2023)Adaptive Storage Optimization Scheme for Blockchain-IIoT Applications Using Deep Reinforcement LearningIEEE Access10.1109/ACCESS.2022.323347411(1372-1385)Online publication date: 2023
  • (2023)A comprehensive survey on reinforcement-learning-based computation offloading techniques in Edge Computing SystemsJournal of Network and Computer Applications10.1016/j.jnca.2023.103669216:COnline publication date: 1-Jul-2023
  • (2022)An Overview of Technologies for Improving Storage Efficiency in Blockchain-Based IIoT ApplicationsElectronics10.3390/electronics1116251311:16(2513)Online publication date: 11-Aug-2022

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          cover image ACM Other conferences
          ACM TURC '21: Proceedings of the ACM Turing Award Celebration Conference - China
          July 2021
          284 pages
          ISBN:9781450385671
          DOI:10.1145/3472634
          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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          Publication History

          Published: 02 October 2021

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          Author Tags

          1. Mobile edge computing
          2. blockchain
          3. cooperation computation
          4. deep reinforcement learning

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          • Refereed limited

          Funding Sources

          • National Natural Science Foundation of China
          • Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission
          • Fundamental Research Funds for the Central Universities under Grant
          • International S&T Cooperation Program of Shanghai Science and Technology Commission under Grant

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          Cited By

          View all
          • (2023)Adaptive Storage Optimization Scheme for Blockchain-IIoT Applications Using Deep Reinforcement LearningIEEE Access10.1109/ACCESS.2022.323347411(1372-1385)Online publication date: 2023
          • (2023)A comprehensive survey on reinforcement-learning-based computation offloading techniques in Edge Computing SystemsJournal of Network and Computer Applications10.1016/j.jnca.2023.103669216:COnline publication date: 1-Jul-2023
          • (2022)An Overview of Technologies for Improving Storage Efficiency in Blockchain-Based IIoT ApplicationsElectronics10.3390/electronics1116251311:16(2513)Online publication date: 11-Aug-2022

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