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Reliable and efficient emergency rescue networks: A blockchain and fireworks algorithm-based approach.
Chen, Bin; Zhang, Weihua; Shi, Yijin; Lv, Di; Yang, Zilan.
  • Chen B; Lijiang Cultural and Tourism College, Lijiang, China.
  • Zhang W; Lijiang Jingcheng Education Training Co., Ltd., Lijiang, China.
  • Shi Y; Lijiang Cultural and Tourism College, Lijiang, China.
  • Lv D; Lijiang Cultural and Tourism College, Lijiang, China.
  • Yang Z; Lijiang Cultural and Tourism College, Lijiang, China.
Comput Commun ; 206: 172-177, 2023 Jun 01.
Article in English | MEDLINE | ID: covidwho-2313572
ABSTRACT
In recent years, coronavirus disease 2019 (COVID-19) has been a severe issue the world faces. Emergency rescue networks concerning the distribution of relief materials have gained extensive attention to tackle COVID-19 and related emergency issues. However, it is challenging to establish reliable and efficient emergency rescue networks due to information asymmetry and lack of trust among different rescue stations. In this work, we propose blockchain-based emergency rescue networks to track every transaction of the relief materials reliably and make decisions to deliver relief materials efficiently. More specifically, we propose a hybrid blockchain architecture that employs on-chain data verification to authenticate data records and off-chain data storage to reduce storage overhead. Furthermore, we propose a fireworks algorithm to efficiently calculate the optimal allocation strategies for relief materials. The algorithm provides chaotic random screening and node request guarantee techniques with good convergence. The simulation results show that integrating blockchain technology and the fireworks algorithm can significantly improve relief materials' operation efficiency and distribution quality.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Randomized controlled trials Language: English Journal: Comput Commun Year: 2023 Document Type: Article Affiliation country: J.comcom.2023.05.005

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Randomized controlled trials Language: English Journal: Comput Commun Year: 2023 Document Type: Article Affiliation country: J.comcom.2023.05.005