PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 14, 2021IEEE Transactions on Industrial Informatics156 citations

A Sharding Scheme-Based Many-Objective Optimization Algorithm for Enhancing Security in Blockchain-Enabled Industrial Internet of Things

View Full Paper
XCXingjuan CaiSGShaojin GengJZJingbo Zhang

Key Points

Key points are not available for this paper at this time.

Abstract

While the industrial Internet of Things (IIoT) can support efficient control of the physical world through large amounts of industrial data, data security has been a challenge due to various interconnections and accesses. Blockchain technology can support security and privacy preservation in IIoT data with its trusted and reliable security mechanism. Sharding technology can help improve the overall throughput and scalability of blockchain networks. However, the effectiveness of sharding is still challenging due to the uneven distribution of malicious nodes. By aiming to improve the performance of blockchain networks and reduce the possibility of malicious node aggregation, in this article, we propose a many-objective optimization algorithm based on the dynamic reward and penalty mechanism (MaOEA-DRP) to optimize the shard validation validity model. Then, an optimal blockchain sharding scheme is obtained. Compared with other state-of-the-art many-objective optimization algorithms, MaOEA-DRP performs better on the DTLZ test suite. The simulation results demonstrate that our proposed algorithm can significantly improve the throughput and validity of sharding for better security in the blockchain-enabled IIoT.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Cai et al. (2021) studied this question.

synapsesocial.com/papers/6a6319043eb69703d1b6f45bhttps://doi.org/10.1109/tii.2021.3051607
Ask AI
Helpful
Bookmark
Share
View Full Paper