UAV-Assisted Computation Offloading Toward Energy-Efficient Blockchain Operations in Internet of Things

Xunqiang Lan, Xiao Tang, Ruonan Zhang, Wensheng Lin, Zhu Han

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The advances in the Internet of Things (IoT) have provided generous opportunities for various applications, yet the data security concerns need to be specially addressed due to the limited capability of IoT devices. Toward this issue, we propose to deploy a blockchain system with practical Byzantine fault tolerance (PBFT) consensus for IoT data security provisioning. In particular, we conduct profound analyses regarding the PBFT procedure and elaborate on the computation burden therein. Then, an unmanned aerial vehicle (UAV) is leveraged to offload the computation and assist the blockchain operations. The system energy efficiency is introduced as the ratio of the blockchained IoT data amount and energy consumption for the computation and communication in the network. Further, we maximize the system energy efficiency by the joint design of offloading and transmission strategies, as well as the UAV deployment, within a reinforcement learning framework. Finally, simulation results are provided to corroborate the effectiveness of our proposal.

Original languageEnglish
Pages (from-to)1469-1473
Number of pages5
JournalIEEE Wireless Communications Letters
Volume12
Issue number8
DOIs
StatePublished - 1 Aug 2023

Keywords

  • Internet of Things
  • blockchain
  • computation offloading
  • deep reinforcement learning
  • unmanned aerial vehicle

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