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Energy‐efficient routing paradigm for resource‐constrained Internet of Things‐based cognitive smart city

The exponential growth in the smart cities and the massive deployment of wireless sensor network‐based Internet of Things (IoT) has resulted in generating the humongous data, which needs to be orchestrated. Further, it is observed that the resource‐constrained IoT devices act as stumbling block in the successful realization of cognitive smart cities. Hence, there is a high need to manage the data transmission from massive IoT devices and also to enhance the productivity of such devices. To address this issue, in this article, we present energy‐efficient routing paradigm for resource‐constrained IoT‐based cognitive smart city (EI‐CSC). We adapt Sooty tern optimization algorithm (STOA) due to its faster convergence and high ‘exploration and exploitation’ capabilities to perform energy efficient cluster‐based routing. We focus primarily on rendering the optimized solution to the cluster head selection problem through STOA. The outcomes of simulation analysis of EI‐CSC promises enhanced performance in the context of stability period and network lifetime by 83.4% and 107.7%, ‘respectively’ as compared to recently proposed ‘genetic algorithm and PSO based hybrid clustering algorithm’.