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An improved DPoS consensus mechanism in blockchain based on PLTS for the smart autonomous multi-robot system.

Authors :
Liu, Jun
Xie, Mingyue
Chen, Shuyu
Ma, Chuang
Gong, Qianhong
Source :
Information Sciences. Oct2021, Vol. 575, p528-541. 14p.
Publication Year :
2021

Abstract

• We build a blockchain for robotic data storage in the multi-robot system for smart autonomous robots. • We propose a novel voting algorithm with probabilistic linguistic information (VAPLI). • A novel score function for probabilistic linguistic term sets is introduced. • A novel deviation degree function for probabilistic linguistic term sets is introduced. Due to the development of robot technology, smart autonomous multi-robot systems face different security problems such as data loss and vulnerabilities. However, the robot information stored in blockchain can be more transparent and effective at ensuring the security of the robot system due to the decentralization, tamper-proof and anonymity of blockchain. In the architectural composition of blockchain, Delegated Proof of Stake (DPoS) consensus mechanism is playing a critical role with more decentralization, lower energy consumption and faster confirmation speed. Similar to the board voting, the holders cast a certain number of delegates to perform verification and block generating on their behalf in DPoS. In order to improve the efficiency and flexibility of DPoS consensus mechanism, we propose an improved DPoS consensus mechanism based on the Probabilistic Linguistic Term Set (PLTS) for the smart autonomous multi-robot system. By adding voting options for nodes, the Voting Algorithm with Probabilistic Linguistic Information (VAPLI) calculates the score and deviation degree of each node after tabulating the voting results. The selection of a delegate is based on the comparison of the score and deviation degree. Finally, we explore the model implementation of the improved DPoS consensus mechanism, and verify its feasibility and effectiveness using examples. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00200255
Volume :
575
Database :
Academic Search Index
Journal :
Information Sciences
Publication Type :
Periodical
Accession number :
152367960
Full Text :
https://doi.org/10.1016/j.ins.2021.06.046