Journal
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Volume 40, Issue 12, Pages 3485-3500Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2022.3213358
Keywords
Cloud-edge-device computing; task offloading; blockchain; reinforcement learning
Funding
- China National Funds for Distinguished Young Scientists [61825204]
- NSFC Project [61932016, 62101301, 62132011, 62132009]
- Beijing Outstanding Young Scientist Program [BJJWZYJH01201910003011]
- China Computer Federation (CCF)-Huawei Populus Euphratica Forest Fund [CCF-HuaweiBC2021005]
- Chinese Association for Artificial Intelligence (CAAI)-Huawei MindSpore Open Fund [CAAIXSJLJJ-2020-014A]
- China Postdoctoral Science Foundation [2021M691787]
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This paper proposes a blockchain-empowered collaborative task offloading method for Cloud-Edge-Device (CED) computing. The blockchain plays a central role in task offloading, resource brokerage, and incentives. By modifying the blockchain consensus process, participants can reach an agreement by solving the task offloading problem. A truthful incentive mechanism is also proposed to encourage resource contributions and honesty in the system.
How to enable high-performance task offloading and preserve the trust between participants is imperative yet nontrivial to the Cloud-Edge-Device (CED) computing, mainly because the resources are geo-distributed and operated by different parties. Also, the CED participants are highly dynamic and heterogeneous in resource provision and may conflict in interest. This paper proposes BlockChain-empowered CED (BCCED), a blockchain-empowered collaborative task offloading for CED computing. In BC-CED, blockchain plays a central role in the main functionality of CED, including task offloading, brokerage of resource usage, and incentives. We distinguish the BC-CED from the existing solutions by modifying the blockchain consensus process, enabling the participants to reach an agreement via solving the task offloading problem. For this purpose, we formulate the offloading problem by considering the computation capabilities of candidate nodes and the network performance. BC-CED allows each participant to apply reinforcement learning-based methods to solve this problem and compete for the right of block output by comparing the offloading policy performance and accepting the best policy as the offloading scheme within the next period. We also propose a truthful incentive mechanism to encourage resource contributions in BC-CED and force them to he honest. Extensive tests by implementing our solutions in a commercialized blockchain platform have shown how BC-CED achieves a superior performance in task offloading and blockchain maintenance.
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