{"title":"Crowdsourcing Work as Mining: A Decentralized Computation and Storage Paradigm","authors":"Canhui Chen, Zerui Cheng, Shutong Qu, Zhixuan Fang","doi":"10.1145/3600061.3603177","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel and energy-efficient blockchain system, CrowdMine, which exploits useful crowdsourcing computation to achieve decentralized consensus. CrowdMine solves user-proposed computing tasks and utilizes the computation committed to the task solving process to secure decentralized on-chain storage. With our designed “Proof of Crowdsourcing Work” (PoCW) protocol, our system provides an efficient paradigm for computation and storage in a trustless and decentralized environment. We also implement the system with 40 distributed nodes to demonstrate its performance and robustness.","PeriodicalId":228934,"journal":{"name":"Proceedings of the 7th Asia-Pacific Workshop on Networking","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th Asia-Pacific Workshop on Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3600061.3603177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose a novel and energy-efficient blockchain system, CrowdMine, which exploits useful crowdsourcing computation to achieve decentralized consensus. CrowdMine solves user-proposed computing tasks and utilizes the computation committed to the task solving process to secure decentralized on-chain storage. With our designed “Proof of Crowdsourcing Work” (PoCW) protocol, our system provides an efficient paradigm for computation and storage in a trustless and decentralized environment. We also implement the system with 40 distributed nodes to demonstrate its performance and robustness.
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