一种应用于边缘计算的区块链分片方案

doi:10.11959/j.issn.2096-3750.2023.00333

Abstract

Abstract:

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.

Key words: blockchain, sharding, edge computing, consensus

CLC Number:

TP309

Jun WANG, Jianwei MA, Jinxi LUO. A blockchain sharding scheme in edge computing[J]. Chinese Journal on Internet of Things, 2023, 7(4): 88-100.

Figures/Tables 10

References 30

[1]	DORRI A , KANHERE S S , JURDAK R . Towards an optimized blockchain for IoT[C]// Proceedings of 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI). Piscataway:IEEE Press, 2017: 173-178.
[2]	CHRISTIDIS K , DEVETSIKIOTIS M . Blockchains and smart contracts for the internet of things[J]. IEEE Access, 2016,4: 2292-2303.
[3]	TAN L , SHI N , YU K P ,et al. A blockchain-empowered access control framework for smart devices in green internet of things[J]. ACM Transactions on Internet Technology, 2021,21(3): 1-20.
[4]	CHEN Z Y , TIAN P , LIAO W X ,et al. Zero knowledge clustering based adversarial mitigation in heterogeneous federated learning[J]. IEEE Transactions on Network Science and Engineering, 2021,8(2): 1070-1083.
[5]	ZHOU B W , DASTJERDI A V , CALHEIROS R N ,et al. A context sensitive offloading scheme for mobile cloud computing service[C]// Proceedings of 2015 IEEE 8th International Conference on Cloud Computing. Piscataway:IEEE Press, 2015: 869-876.
[6]	WANG H , XIE Q , ZHAO Q ,et al. A model-driven deep neural network for single image rain removal[C]// Proceedings of 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Piscataway:IEEE Press, 2020: 3100-3109.
[7]	ZHANG Z H , FENG J , PEI Q Q ,et al. Integration of communication and computing in blockchain-enabled multi-access edge computing systems[J]. China Communications, 2021,18(12): 297-314.
[8]	REN Y J , LENG Y , CHENG Y P ,et al. Secure data storage based on blockchain and coding in edge computing[J]. Mathematical Biosciences and Engineering:MBE, 2019,16(4): 1874-1892.
[9]	FERNáNDEZ-CARAMéS T M , FRAGA-LAMASP . A review on the use of blockchain for the internet of things[J]. IEEE Access, 2018(6): 32979-33001.
[10]	LUU L , NARAYANAN V , ZHENG C D ,et al. A secure sharding protocol for open blockchains[C]// Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. New York:ACM Press, 2016: 17-30.
[11]	WANG J , WANG H . MONOXIDE . Scale out blockchains with asynchronous consensus zones[EB]. 2019.
[12]	REN Z J , CONG K L , AERTS T ,et al. A scale-out blockchain for value transfer with spontaneous sharding[C]// Proceedings of 2018 Crypto Valley Conference on Blockchain Technology (CVCBT). Piscataway:IEEE Press, 2018: 1-10.
[13]	GUO H , LI W X , NEJAD M ,et al. Access control for electronic health records with hybrid blockchain-edge architecture[C]// Proceedings of 2019 IEEE International Conference on Blockchain (Blockchain). Piscataway:IEEE Press, 2020: 44-51.
[14]	GAI K K , WU Y L , ZHU L H ,et al. Differential privacy-based blockchain for industrial internet of things[J]. IEEE Transactions on Industrial Informatics, 2020,16(6): 4156-4165.
[15]	ZHOU Z Y , WANG B C , DONG M X ,et al. Secure and efficient vehicle-to-grid energy trading in cyber physical systems:integration of blockchain and edge computing[J]. IEEE Transactions on Systems,Man,and Cybernetics:Systems, 2020,50(1): 43-57.
[16]	LI C , LIANG S Y , ZHANG J . Blockchain-based data trading in edge-cloud computing environment[J]. Information Processing ＆Management, 2022,59(1): 102786.
[17]	XU X L , ZHANG X Y , GAO H H ,et al. BeCome:blockchain-enabled computation offloading for IoT in mobile edge computing[J]. IEEE Transactions on Industrial Informatics, 2020,16(6): 4187-4195.
[18]	KOKORIS-KOGIASE , JOVANOVIC P , GASSER L ,et al. O mniLedger:asecure,scale-out,decentralized ledger via sharding[C]// Proceedings of 2018 IEEE Symposium on Security and Privacy (SP). Piscataway:IEEE Press, 2018: 583-598.
[19]	DANG H , DINH T T A , LOGHIN D ,et al. Towards scaling blockchain systems via sharding[C]// Proceedings of the 2019 International Conference on Management of Data. New York:ACM Press, 2019: 123-140.
[20]	SABT M , ACHEMLAL M , BOUABDALLAH A . Trusted execution environment:what it is,and what it is not[C]// Proceedings of 2015 IEEE Trustcom/BigDataSE/ISPA. Piscataway:IEEE Press, 2015: 57-64.
[21]	YANG L , ZHOU W , ZHANG W . EdgeShare:a blockchain-based edge data-sharing framework for industrial internet of things[J]. Neurocom puting, 2022,485: 219-232.
[22]	ZHANG L , ZHOU Y , WANG W . Resource allocation and trust computing for blockchain-enabled edge computing system[J]. Computers＆Security, 2021,105:102249.
[23]	GAO N J , HUO R , WANG S ,et al. Sharding-hashgraph:a high-performance blockchain-based framework for industrial internet of things with hashgraph mechanism[J]. IEEE Internet of Things Journal, 2022,9(18): 17070-17079.
[24]	刘炜, 阮敏捷, 佘维 ,等. 面向物联网的PBFT优化共识算法[J]. 计算机科学, 2021,48(11): 151-158.
	LIU W , RUAN M J , SHE W ,et al. PBFT optimized consensus algorithm for internet of things[J]. Computer Science, 2021,48(11): 151-158.
[25]	SINAGA K P , YANG M S . Unsupervised K-means clustering algorithm[J]. IEEE Access, 2020(8): 80716-80727.
[26]	BUCHMAN E , KWON J , MILOSEVIC Z ,et al. The latest gossip on BFT consensus[EB]. 2018.
[27]	AVCI O , ABDELJABER O , KIRANYAZ S . Wireless and real-time structural damage detection:a novel decentralized method for wireless sensor networks[J]. Journal of Sound and Vibration, 2018,424: 158-172.
[28]	MICALI S , RABIN M , VADHAN S . Verifiable random functions[C]// Proceedings of 40th Annual Symposium on Foundations of Computer Science (Cat.No.99CB37039). Piscataway:IEEE Press, 2002: 120-130.
[29]	ANDROULAKI E , BARGER A , BORTNIKOV V ,et al. Hyperledger fabric:a distributed operating system for permissioned blockchains[C]// Proceedings of the Thirteenth EuroSysConference. New York:ACM Press, 2018: 1-15.
[30]	LUO C R , HU Y Y , ZHANG S ,et al. Fission:autonomous,scalable sharding for IoT blockchain[C]// Proceedings of 2022 IEEE 46th Annual Computers,Software,and Applications Conference (COMPSAC). Piscataway:IEEE Press, 2022: 956-965.

Metrics

Recommended 0

No Suggested Reading articles found!

A blockchain sharding scheme in edge computing

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 30

Related Articles 15

Metrics

Recommended 0

[1]	Peiyan YUAN, Saike SHAO, Ran WEI, Junna ZHANG, Xiaoyan ZHAO. Research on the cooperative offloading strategy of sensory data based on delay and energy constraints [J]. Chinese Journal on Internet of Things, 2023, 7(1): 109-117.
[2]	Yao LIU, Yueyuan HE, Hongjing ZHOU, Chaoliang LI, Chuang LI. Partial computation offloading method based on joint resource allocation for mobile edge computing [J]. Chinese Journal on Internet of Things, 2023, 7(1): 140-148.
[3]	Lin SU, Xiaochao DANG, Zhanjun HAO, Chunrui RU, Xu SHANG. Dynamic adaptive offloading method based on WPT-MEC [J]. Chinese Journal on Internet of Things, 2022, 6(4): 128-138.
[4]	Xian LI, Suzhi BI, Hongru ZENG, Bin LIN, Xiaohui LIN. Collaborative task offloading and resource allocation optimization for intelligent edge devices [J]. Chinese Journal on Internet of Things, 2022, 6(4): 41-52.
[5]	Weijin JIANG, Tiantian LUO, Ying YANG, En LI, Wenying ZHOU. Private data access control model based on block chain technology in the internet of things environment [J]. Chinese Journal on Internet of Things, 2022, 6(4): 169-182.
[6]	Chuannian SHEN. Review on cross-chain technology research of blockchains [J]. Chinese Journal on Internet of Things, 2022, 6(4): 183-196.
[7]	Jun SUN, Shangweikang ZHAO. Energy-saving computation offloading scheme based on Sarsa algorithm in industrial internet of things [J]. Chinese Journal on Internet of Things, 2022, 6(3): 82-90.
[8]	Meinan ZHANG, Mingqi ZHANG, Fei DING, Hengheng ZHUANG, Hairong MA. Offloading strategy with edge optimization of time delay and energy consumption in integrated satellite-terrestrial relay network [J]. Chinese Journal on Internet of Things, 2022, 6(3): 124-132.
[9]	Yangqun LI, Dengyin ZHANG. Research and application of Web of things resource management framework [J]. Chinese Journal on Internet of Things, 2022, 6(2): 50-64.
[10]	Juan FANG, Zhiyuan YE, Mengyuan ZHANG, Jiamei SHI, Ziyi TENG. Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario [J]. Chinese Journal on Internet of Things, 2022, 6(1): 91-100.
[11]	Xin SU, Su JIANG, Yiqing ZHOU. Research on location privacy protection of mobile terminals for maritime monitoring sensor networks [J]. Chinese Journal on Internet of Things, 2021, 5(4): 26-36.
[12]	Deze ZENG, Lvhao CHEN, Lin GU, Yuepeng LI. Cloud native based edge computing: vision and challenges [J]. Chinese Journal on Internet of Things, 2021, 5(2): 7-17.
[13]	Qi ZHANG, Yuna JIANG, Xiaohu GE, Yonghui LI. Resource allocation based on optimal transport theory in IoT edge computing [J]. Chinese Journal on Internet of Things, 2021, 5(2): 60-70.
[14]	Hao YUAN, Deke GUO, Guoming TANG, Lailong LUO. Online energy-aware task dispatching with QoS guarantee in edge computing [J]. Chinese Journal on Internet of Things, 2021, 5(2): 71-77.
[15]	Jing LU, Hanlin LI, Lin GAO. Design of task dividing and offloading algorithm in mobile edge computing [J]. Chinese Journal on Internet of Things, 2021, 5(2): 78-86.