Edge Computing and Lightning Network Empowered Secure Food Supply Management

Keke Gai, Zhengkang Fang, Ruili Wang, Liehuang Zhu, Peng Jiang, Kim Kwang Raymond Choo

Research output: Journal PublicationArticlepeer-review

17 Citations (Scopus)

Abstract

The recent COVID-19 pandemic has highlighted the importance of food safety and supply chain governance. In other words, we need to ensure traceability along the supply chain and support high-frequency transactions, effective data collections, etc. Thus, we posit the potential of using a lightning network, which is a decentralized traceable paradigm for achieving high-frequency transactions in blockchain-based systems. In addition, we also utilize edge computing to help facilitate data collection. However, a key challenge in securing food supplies is determining the optimal global transaction path in the lightning network while achieving efficiency and meeting the dynamic nature of food supply management. Thus, we propose a blockchain-edge scheme that utilizes our proposed dynamic programming to produce optimal solutions for selecting global transaction paths. Specifically, our scheme optimizes routing fees under existing constraints (e.g., transmission cost, computing resource consumption, and lightning network balance). The findings from our evaluations demonstrate the utility of our proposed approach in facilitating food safety management.

Original languageEnglish
Pages (from-to)14247-14259
Number of pages13
JournalIEEE Internet of Things Journal
Volume9
Issue number16
DOIs
Publication statusPublished - 15 Aug 2022
Externally publishedYes

Keywords

  • Blockchain
  • dynamic programming
  • edge computing
  • food supply management
  • lightning network
  • optimization

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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