Development of Dual Cluster Head Selection Mechanism in WSN Based on IoT for Energy-Efficient Data Transmission in Smart City Applications.

The Internet of Things (IoT) in a smart city has faced various issues while providing better outperformance as well as energy optimization. Moreover, the nodes are usually grouped as clusters in both the Wireless Sensor Networks (WSNs) and IoT which may lead to the formation of a Cluster Head (CH), which has gathered data from other nodes and communicates with the Base Station (BS). Moreover, the sensor nodes over the WSN-dependent IoT network have been constraining. A clustering process has provided an effective solution to extend the lifespan of the model by organizing the nodes into clusters. Moreover, the classical clustering process suffers from various issues that affect the performance of this model. Hence, a new plan is made in this proposal to design a novel dual CH selection protocol in WSN using IoT in smart cities. In this dual CH selection, the first CH selection is made using certain objective constraints like distance, delay, energy, packet loss, and transmission load using the optimization strategy with Cat and Mouse with Krill Herd Optimization (CMKHO) via Cat and Mouse Based Optimizer (CMO) and Krill Herd Optimization (KHO). Then, the second CH is selected concerning the objective constraint like distance between two CHs and energy for data transmission using the same CMKHO. Here, the first CH selection sends the data to the sink node (BS) and at that time, if more data packets are involved in the transmission, energy loss may occur due to overload. To solve this energy loss problem, the data from the first CH is transmitted to the second CH, and from the second CH, the data is sent to the sink node, which balances the transmission energy between the first and second CH which further extends the lifetime of the WSN. The experimental analysis is done on the developed dual CH selection in WSN with IoT to show a better lifetime as well as energy when assimilated with other techniques when utilizing it in the applications of smart cities. [ABSTRACT FROM AUTHOR]