Simulation and Evaluation of Distributed consensus Network for Multi-Agent Systems for Sybil Attacks

Abstract

Distributed average consensus represents the amount of computing of inputs held by multiple agents that communicate through peer-to-peer networks. Collaboration among operators is essential for any distributed standard consensus protocol as every specialist needs to contribute to different operators, typically the adjacent (neighbouring) operators. Internet-of-Things (IoT) implementation is challenging because of its heterogeneous, massively distributed nature. The challenges of this challenge can be addressed with blockchain-based platforms and technologies. Testing and evaluation platforms are required for Blockchain deployments in IoT. A realistic and configurable network environment is presented in this paper to evaluate consensus algorithms. Many blockchainevaluation platforms do not provide a configurable and realistic network environment or are tied to a specific consensus protocol. With our simulator, practitioners can evaluate how consensus algorithms affect network events in congested or contested scenarios to determine the best consensus algorithm. It is proposed to achieve this task by generalizing consensus methods. The Blockchain simulator employs Discrete event network simulations for increased fidelity and scalability. In addition to evaluating the time, state block rate (%), estimation error, average throughput, and simulation time, we evaluate the performance of the proposed techniques based on the number of peer nodes. A comparison of the average transaction delivery rate with a traditional protocol is shown. The proposed protocol has a higher throughput average than the traditional one.