Reputation-Based Sharding Consensus Model in Information-Centric Networking

Abstract

The various integration systems of blockchain and information-centric network (ICN) have been applied to provide a trusted and neutral approach to cope with large-scale content distribution in IoT, AR/VR, or 5G/6G scenarios. As a result, the scalability problem of blockchain has been an increasing concern for researchers. The sharding mechanism is recognized as a promising approach to address this challenge. However, there are still many problems in the existing schemes. Firstly, real-time processing speed trades off security of validation. Secondly, simply randomly assigning nodes to the shards may make nodes located very far from each other, which increases the block propagation time and reduces the efficiency advantage brought by the sharding mechanism. Therefore, we optimize a reputation-based sharding consensus model by multi-dimension trust and leverage the affinity propagation (AP) algorithm for gathering consensus nodes into shards. Given the minimal possibility to be at fault in the security of validation, clients can achieve real-time processing speed with assurance. The evaluation results show that the normalized mean square error (NMSE) between the estimated reputation value and the real reputation value of our reputation scheme is less than 0.02. Meanwhile, compared with the classical sharding scheme Omniledger, TPS performance can achieve 1.4 times promotion in the case of a large-scale blockchain network of 1000 nodes.