FIBFT: An Improved Byzantine Consensus Mechanism for Edge Computing

Abstract

Blockchain has been widely used to solve data privacy and security issues in edge computing scenarios. However, the blockchain based on edge computing still has some performance problems, such as insufficient scalability, difficulty in balancing security and edge device power consumption, and inability to simultaneously meet low latency, high throughput, high security and privacy issues, etc. In order to solve these problems, this paper proposes a generally improved Byzantine consensus mechanism based on the K-medoids clustering algorithm - FIBFT. Considering the different performance characteristics of each node in the network, the node’s state is first abstracted into a multi-dimensional state space containing eigenvalues, and then the nodes are divided into subnets by the efficient K-medoids clustering algorithm. Each subnet uses a Byzantine consensus mechanism based on arbitration for consensus and data interaction, and the consensus data could be exchanged between the subnets without interfering with the consensus process. The research results show that FIBFT has better scalability and throughput while ensuring high security compared with the traditional Byzantine consensus algorithm.