A Blockchain Distributed Computing Resource Scheduling Balancing Method Based on Variance Ratio
Xiaofeng Chen, Xiangjuan Jia, Lu Zhang, Liang Cai · 2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) · 2022
In this paper, we propose a variance ratio-based blockchain distributed computing resource scheduling and balancing method, in which the tasks processed by each distributed computing engine are clustered and sampled, and the variance ratio of the changes of the distributed computing engine is generated based on the results of the clustered sampling, so that the computing resources can be adjusted to different nodes based on the variance ratio and the post-adjustment verification. It can better ensure that each node has sufficient computing power and minimize the waste of computing resources, thus helping to balance the scheduling of blockchain distributed computing resources.