To improve scalability with Boolean matrix using efficient gossip failure detection and consensus algorithm for PeerSim simulator in IoT environment

• Published in: International journal of information technology (Singapore. Online) 2022, Vol.14 (5), p.2297-2307
• Main Authors: Kumar, Surendra, Samriya, Jitendra Kumar, Yadav, Arun Singh, Kumar, Mohit
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Computer Imaging; Computer Science; Image Processing and Computer Vision; Machine Learning; Original Research; Pattern Recognition and Graphics; Software Engineering; Vision
• ISSN: 2511-2104; 2511-2112
• DOI: 10.1007/s41870-022-00989-8

Recent years have seen a rise in interest in peer-to-peer applications because of their scalability, fault tolerance, and other noteworthy benefits. The main benefit of P2P technology is the reduction of central server resources used by ensuring that computing resources, bandwidth resources, content resources, and so on, are consumed effectively by terminal computers. A distributed computing system or multi-agent system requires global consensus on some synchronization, an action, a decision or data value. The proposed method combines MPI_Comm_shrink() and MPI_Comm_agree() functions with the epidemic gossip protocol, which is a randomly generated paradigm of computation and communication that is both fault-tolerant and scalable. A simulation of an extreme-scale information dissemination process, used in this experimental research, shows that global agreement can be achieved. Event-based PeerSim simulator is used in the article to explore resource discovery mechanisms. Scholars have only presented a few thousand cases of HPC fault detection and agreement in the state-of-the-art literature, in contrast to proposed algorithm (Algorithm 1) exhibited high scalability and bandwidth even as the system size increased up to ten lakh nodes.