Entropy Weighted-Based (EWB) I-LEACH Protocol for Energy-Efficient IoT Applications

The Internet of Things (IoT) is one of the emerging applications in the Wireless Sensor Networks (WSNs). The major concern in WSN is the limited battery power, which can be overcome by selecting the effective cluster head (CH) for the transmission of data in the network. In this paper, an entropy weighted-based I-LEACH protocol is developed for the selection of the CH. The proposed entropy weighted-based I-LEACH protocol is developed by modifying the standard LEACH protocol with the entropy weight. Initially, the IoT nodes are grouped together to form clusters, which is followed by the selection of the cluster head (CH) for the transmission of the data packets to the base station (BS). The CH is selected depending on the threshold value, which is based on the entropy function. The performance metrics, such as number of alive nodes and energy is used for evaluating the effectiveness of the proposed entropy weighted-based (EWB) I-LEACH protocol. The proposed EWB I-LEACH protocol obtained a maximal alive nodes of 11 and maximal energy of 0.1138 J for 50 nodes under dual-slop channel model and obtained a maximal alive nodes of 9 and maximal energy of 0.1116 J for 50 nodes by considering log normal shadowing channel model when compared to the existing protocols.

I. Introduction

The advancements in the technology have increased the massive growth of the sensing applications and devices. In general, Wireless Sensor Network (WSN) gained significance in the network technology and it is undergoing enhancements in faster manner [5]. The IoT is the system that has interconnection with the computing devices, digital or mechanical instruments, personal and similar kind entities. The WSN-based IoT nodes provide restricted storage volume, processing, bandwidth and battery power [6]. Although the WSN has rechargeable battery power, the sensors are kept apart in order to schedule the energy deployment aptly. [7]. While designing a WSN, the reduction in the consumption of power is considered as a crux issue. The routing algorithm is developed to extend the longevity in the network. A group of sensing nodes or the clusters are built in the clustering process for collecting the data and transferring it to the corresponding CH, which is followed by the transmission of the fused data to the BS or the sink node.