A Blockchain Platform of Crowdsensing for Cloud Reallocation
Year: 2025
Type: article
Abstract: This paper proposes a decentralized blockchain-based crowdsensing platform for dynamic cloud resource reallocation and pricing. By integrating supervised linear regression with auction theory, the system enables fair and efficient cloud trading based on user reputation values. In this model, secondary users (buyers) bid for idle cloud resources offered by primary users (sellers), while crowd sensors detect resource availability and feed real-time data into the blockchain. A smart contract-driven incentive mechanism ensures high-quality data collection and trustworthy transactions. The proposed model employs supervised learning to classify and allocate resources, using a modified Vickrey-Clarke-Groves (VCG) pricing mechanism based on critical value theory. Experimental results demonstrate the model's high accuracy, fairness, and resource utilization. It has potential to optimize cloud allocation while performing economic efficiency and algorithmic truthfulness.
DOI: 10.63646/jzei5817
Authors: Yisong Chen, Jin Li
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409732392