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Framework and algorithms for identifying honest blocks in blockchain


Autoři: Xu Wang aff001;  Guohua Gan aff003;  Ling-Yun Wu aff001
Působiště autorů: Key Laboratory of Management, Decision and Information Systems, Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China aff001;  School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China aff002;  Laboratory of Big Data and Blockchain, National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing, China aff003;  Beijing Taiyiyun Technology Co., Ltd., Beijing, China aff004;  University of Science & Technology Beijing, Beijing, China aff005
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0227531

Souhrn

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.

Klíčová slova:

Data management – Markov models – Algorithms – Finance – Internet – Valleys – Graph theory – Directed acyclic graphs


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