Blockchain-based Data Trading in Edge-cloud Computing Environment. Issue 1 (January 2022)

• Record Type: Journal Article
• Authors: Li, Chunlin; Liang, SongYu; Zhang, Jing; Wang, Qiao-e; Luo, Youlong
• Is Part Of: Information processing & management. Volume 59:Issue 1(2022)
• Publication Date: 2022-01
• Subjects: Edge-cloud environment -- Blockchain -- Data trading; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2021.102786
• Languages: English
• ISSNs: 0306-4573

Abstract

Highlights: This paper proposes a secure cost-aware data caching algorithm based on blockchain. The quantum particle swarm optimization mechanism is designed to optimize data caching placement problem. This paper also proposes a secure decentralized data trading algorithm based on blockchain. An iterative double auction mechanism is proposed to improve the efficiency of data trading, maximize social welfare. The performance of the algorithm is evaluated through a large number of experiments. Abstract: With the continuous growth in the amount of data generated in the edge-cloud environment, security risks in traditional centralized data management platforms have been concerned. Blockchain technology can be applied to guarantee safety and information transparency in data caching and trading processes. Therefore, a blockchain-based secure cost-aware data caching scheme is proposed to optimize the placement and prevent the tampering of cache data. In this scheme, under the constraints of transmission cost, edge cache size, a quantum particle swarm optimization (QPSO) algorithm is used to solve the data cache placement problem with the greatest content caching gain. A blockchain-based secure decentralized data trading model is proposed to solve the trust problem among the buyers, sellers, and agent nodes and increase incentives for users to trade data. A double auction mechanism is used to maximize social welfare. The experimental results reveal that the proposed data caching and trading scheme can reduce the data transmission cost, improve the cache hit ratio, and maximize social welfare.