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The most crucial design constraint on the Internet of Things (IoT) enabled wireless sensor networks (WSNs) is energy dissipation. The inefficient data collection by the resource constraint sensors becomes a major roadblock in energy preservation to achieve network longevity. The energy of nodes has to be utilized in an efficient manner which helps in increasing the longevity of WSNs. Clustering is a technique that can utilize the energy of the sensors efficiently by maintaining load balancing among the sensors for increasing the lifetime and scalability of the networks. In this paper, the energy consumption of the network is improved by considering the Genetic Algorithm evolutionary computing technique. The proposed OptiGACHS protocol describes the improved cluster head (CH) selection procedure by incorporating criteria of distance, density, energy, and heterogeneous node’s capability for developing fitness …