一种应用于边缘计算的区块链分片方案  

A blockchain sharding scheme in edge computing

作　　者：王珺[1] 马建炜 罗金喜 WANG Jun;MA Jianwei;LUO Jinxi(School of Communication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)

机构地区：[1]南京邮电大学通信与信息工程学院,江苏南京210003

出　　处：《物联网学报》2023年第4期88-100,共13页Chinese Journal on Internet of Things

基　　金：江苏省重点研发计划(No.BE2020084-5);江苏省研究生科研与实践创新计划(No.46006CX21732)。

摘　　要：边缘计算的数据安全性低和隐私性差等问题制约了边缘计算的发展,区块链可以利用自身的难以篡改性为边缘计算场景中的数据提供安全保障,同时利用可追溯性保护隐私,但是区块链的扩展性瓶颈成为其应用于边缘计算领域的障碍。针对区块链应用于边缘计算时无法满足大量节点同时处理数据的需求的问题,提出了一种符合边缘计算场景需求的双层分片方案,用改进的K-means算法实现节点基于地理位置的分片,并结合权益委托证明(DPoS,delegated proof of stake)与实用拜占庭容错(PBFT,practical Byzantine fault tolerance)的思想设计了一种局部区块链网络共识(LBNC,local blockchain network consensus)算法达成片内共识,通过多分片并行处理交易的方式提高系统能容纳的节点数量。仿真结果表明,所提方案比PBFT有更低的时延和更高的吞吐量,并且总吞吐量随分片数量增加。The low security and poor privacy of the data in edge computing restrict the development of edge computing.Block chains can provide security for data in edge computing using their own tamper resistance,while protecting privacy by use of traceability.But the bottleneck of blockchain's scalability has become a barrier to their application in the field of edge computing.To solve the problem that blockchain can not meet the needs of a large number of nodes to process data at the same time when applied to edge computing,a two-layer sharding scheme was presented,which meets the needs of edge computing scenarios.Geographic location-based partitioning of nodes was implemented using the improved K-means algorithm,and a local blockchain network consensus(LBNC)algorithm was designed based on the idea of delegated proof of stake(DPoS)and practical Byzantine fault tolerance(PBFT).Simulation results show that the proposed scheme has less delay and higher throughput than those of PBFT,and the total throughput increases with the number of shards.

关 键 词：区块链 分片 边缘计算 共识 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]