{"title":"一个轻量级的本地可修复的基于代码的区块链存储架构","authors":"Wanning Bao, Liangmin Wang, Jie Chen","doi":"10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00324","DOIUrl":null,"url":null,"abstract":"The blockchain system requires every node to preserve a complete copy of data arbitrarily, which exerts tremendous storage pressure on nodes. Some researchers applied the erasure code to reduce storage redundancy. However, code storage schemes have the problem of inefficient data communication while verifying transactions and downloading data. To solve this problem, this paper proposes a lightweight locally repairable code (LRC) storage scheme inspired by the idea of slice strategy from privacy computing. Firstly, partitioning each block into distinct transaction slices substantially reduces the amount of transmitted data required to verify a transaction. Secondly, our scheme can recover single-point data with fewer code data slices by local nodes and with less network communication overhead. At last, we analyze the performance of our scheme from theoretical perspectives and examine the storage performance and computation efficiency of our scheme from experimental perspectives. Results suggest that our scheme can effectively reduce the storage overhead while also decreasing the network communication overhead and improving the data reading efficiency.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Lightweight Locally Repairable Code-based Storage Architecture for Blockchains\",\"authors\":\"Wanning Bao, Liangmin Wang, Jie Chen\",\"doi\":\"10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00324\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The blockchain system requires every node to preserve a complete copy of data arbitrarily, which exerts tremendous storage pressure on nodes. Some researchers applied the erasure code to reduce storage redundancy. However, code storage schemes have the problem of inefficient data communication while verifying transactions and downloading data. To solve this problem, this paper proposes a lightweight locally repairable code (LRC) storage scheme inspired by the idea of slice strategy from privacy computing. Firstly, partitioning each block into distinct transaction slices substantially reduces the amount of transmitted data required to verify a transaction. Secondly, our scheme can recover single-point data with fewer code data slices by local nodes and with less network communication overhead. At last, we analyze the performance of our scheme from theoretical perspectives and examine the storage performance and computation efficiency of our scheme from experimental perspectives. Results suggest that our scheme can effectively reduce the storage overhead while also decreasing the network communication overhead and improving the data reading efficiency.\",\"PeriodicalId\":43791,\"journal\":{\"name\":\"Scalable Computing-Practice and Experience\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scalable Computing-Practice and Experience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00324\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scalable Computing-Practice and Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00324","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
A Lightweight Locally Repairable Code-based Storage Architecture for Blockchains
The blockchain system requires every node to preserve a complete copy of data arbitrarily, which exerts tremendous storage pressure on nodes. Some researchers applied the erasure code to reduce storage redundancy. However, code storage schemes have the problem of inefficient data communication while verifying transactions and downloading data. To solve this problem, this paper proposes a lightweight locally repairable code (LRC) storage scheme inspired by the idea of slice strategy from privacy computing. Firstly, partitioning each block into distinct transaction slices substantially reduces the amount of transmitted data required to verify a transaction. Secondly, our scheme can recover single-point data with fewer code data slices by local nodes and with less network communication overhead. At last, we analyze the performance of our scheme from theoretical perspectives and examine the storage performance and computation efficiency of our scheme from experimental perspectives. Results suggest that our scheme can effectively reduce the storage overhead while also decreasing the network communication overhead and improving the data reading efficiency.
期刊介绍:
The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.