Fengqi Li;Jiaheng Wang;Weilin Xie;Ning Tong;Deguang Wang
{"title":"X-RAFT: Improve RAFT Consensus to Make Blockchain Better Secure EdgeAI-Human-IoT Data","authors":"Fengqi Li;Jiaheng Wang;Weilin Xie;Ning Tong;Deguang Wang","doi":"10.1109/TETC.2024.3472059","DOIUrl":null,"url":null,"abstract":"The proliferation of IoT devices, advancements in edge computing, and innovations in AI technology have created an ideal environment for the birth and growth of Edge AI. With the trend towards the Internet of Everything (IoE), the EdgeAI- Human-IoT architectural framework highlights the necessity for efficient data exchange interconnectivity. Ensuring secure data sharing and efficient data storage are pivotal challenges in achieving seamless data interconnection. Owing to its simplicity, ease of deployment, and consensus-reaching capabilities, the RAFT consensus algorithm, which is commonly used in distributed storage, faces limitations as the IoT scale expands. The computational, communication, and storage capabilities of nodes are constraints, and the security of data remains a concern. To address these complex challenges, we introduce the X-RAFT consensus algorithm, which is tailored for blockchain technology. This algorithm enhances system performance and robustness, mitigates the impact of system load, enhances system sustainability, and increases Byzantine fault tolerance. Through analysis and simulations, our proposed solution has been evidenced to provide reliable security and efficient performance.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"13 1","pages":"22-33"},"PeriodicalIF":5.1000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Emerging Topics in Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10720701/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The proliferation of IoT devices, advancements in edge computing, and innovations in AI technology have created an ideal environment for the birth and growth of Edge AI. With the trend towards the Internet of Everything (IoE), the EdgeAI- Human-IoT architectural framework highlights the necessity for efficient data exchange interconnectivity. Ensuring secure data sharing and efficient data storage are pivotal challenges in achieving seamless data interconnection. Owing to its simplicity, ease of deployment, and consensus-reaching capabilities, the RAFT consensus algorithm, which is commonly used in distributed storage, faces limitations as the IoT scale expands. The computational, communication, and storage capabilities of nodes are constraints, and the security of data remains a concern. To address these complex challenges, we introduce the X-RAFT consensus algorithm, which is tailored for blockchain technology. This algorithm enhances system performance and robustness, mitigates the impact of system load, enhances system sustainability, and increases Byzantine fault tolerance. Through analysis and simulations, our proposed solution has been evidenced to provide reliable security and efficient performance.
期刊介绍:
IEEE Transactions on Emerging Topics in Computing publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT.