Distributed Mimic Judgment Algorithm based on Multi-Strategy Decentralization Model

The current mimic adjudication model is centered on a single adjudicator, and the adjudication algorithm is relatively single and static, which cannot cope with today's complex and changeable network environment. First, a distributed adjudication model is proposed to decentralize the adjudicator, each sub-arbiter is different from the previous use of all executive results, but randomly selects the output of the executive as the input incentive. Secondly, based on this model, a consensus mechanism algorithm is proposed to iteratively normalize the local adjudication results of the sub-arbiters to achieve the global optimal adjudication result. The analysis of the simulation experiment results shows that the algorithm proposed in this paper is more accurate than the traditional adjudication algorithm when multiple executors are online. The algorithm can further reduce the risk of common-mode escape and improve the security of the mimic defense system.