Metaheuristics-based routing optimisation, balanced workload distribution and security strategy in IoT environment

Abstract

The advancement of wireless sensor networks (WSNs) made the society ever so slightly gain new degrees of freedom, intrinsically with respect to connectivity. The emergence of internet of things (IoT) together with the onset and development of evolutionary computing, address the various needs of the growing urbanisation with a significant allusion altogether. Applications built on cloud infrastructure are deployed for job segregation, rapid processing and utilisation but with limitation of proper computation in high density IoT environment. This paper strives on resolving some of the issues so accosted by the IoT paradigm, with the help of a new metaheuristics-based data routing hybrid algorithm based on directed artificial bat algorithm (DABA) and particle swarm optimisation (PSO) to optimise connection issues such as real time delay and network congestion. This approach also introduces the clustering concept together with fog computing to distribute the network stress and to optimise the usage of bandwidth using the dynamic graph partitioning algorithm. The paper further proposes advance metaheuristics constricted PSO (C-PSO) in the hybrid algorithm and effective proposal for security strategy to enhance the efficiency of the IoT environment.