A middleware approach for reliable resource selection on Internet‐of‐Things

Abstract

SummaryDecision making plays a vital role in the selection of resources so that they actively participate for communication and computation on the Internet‐of‐Things platform. For the same, they require the elimination of the challenges related to knowledge representation, discovery, trust, and security due to continuously changing mobility patterns, heterogeneity, interoperability, and scalability on the network. To address the challenges, a novel three‐layered approach, namely, middleware approach for reliable resource selection on Internet‐of‐Things (MARRS‐IoT), is proposed. It performs a search through neighbor discovery algorithm and evaluates trust score of the discovered resources, both locally and globally using fuzzy‐decision algorithm and performs efficient communication among resources via hybrid M‐gear protocol. The approach is simulated and compared against algorithms, namely, particle swarm optimization, ants colony optimization, and binary genetic to evaluate its performance. The obtained results support the efficacy of the MARRS‐IoT with respect to throughput and execution time.