Framework and algorithms for identifying honest blocks in blockchain

Xu Wang, Guohua Gan and Ling-Yun Wu

PLOS ONE, 2020, vol. 15, issue 1, 1-14

Abstract: Blockchain technology gains more and more attention in the past decades and has been applied in many areas. The main bottleneck for the development and application of blockchain is its limited scalability. Blockchain with directed acyclic graph structure (BlockDAG) is proposed in order to alleviate the scalability problem. One of the key technical problems in BlockDAG is the identification of honest blocks which are very important for establishing a stable and invulnerable total order of all the blocks. The stability and security of BlockDAG largely depends on the precision of honest block identification. This paper presents a novel universal framework based on graph theory, called MaxCord, for identifying the honest blocks in BlockDAG. By introducing the concept of discord, the honest block identification is modelled as a generalized maximum independent set problem. Several algorithms are developed, including exact, greedy and iterative filtering algorithms. The extensive comparisons between proposed algorithms and the existing method were conducted on the simulated BlockDAG data to show that the proposed iterative filtering algorithm identifies the honest blocks both efficiently and effectively. The proposed MaxCord framework and algorithms can set the solid foundation for the BlockDAG technology.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0227531

DOI: 10.1371/journal.pone.0227531

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