An Energy-Efficient Data Collection Protocol for IoT Networks Using Social Network Search Metaheuristic

IoT technology is gaining popularity as more affordable, intelligent, and multifunctional IoT devices are developed. The proliferation of these IoT objects has led to their adoption in several areas, including agriculture, livestock farming, health monitoring, etc. The ultimate goal of deploying IoT networks is to collect data for decision-making. Data collection is, therefore, one of the important tasks in IoT networks. The main characteristic of IoT devices is that they are energy-constraints with finite-lifetime batteries. The batteries in IoT devices are not rechargeable, rendering them unusable when they run out. Moreover, for critical applications, the replacement of faulty IoT devices is a tricky operation. Therefore, it is important to control the energy consumption of the IoT devices during data collection in the network to ensure battery longevity. In this paper, we propose the Social Network Search-Based Data Collection Protocol (SNS-DCP), which uses the Social Network Search metaheuristic to create an optimal partition with suitable partition head node selection, thereby optimizing network lifetime and maximizing data collection in IoT networks. The simulation results show that the SNS-DCP protocol outperforms the existing PSO-UFC, PSO-ECHS, and LEACH protocols in terms of network lifetime, number of alive nodes, network energy consumption, and the amount of data collected at the BS. Concisely, the SNS-DCP protocol enhances the data collection by 43%, 68%, and 87% over the PSO-UFC. PSO-ECHS. and LEACH protocols, respectively,