Energy Efficient Data Aggregation Scheme using Improved LEACH Algorithm for IoT Networks

Abstract

The Internet of Things makes it possible to have connected buildings, businesses, and intelligent homes by merging embedded technology, wireless sensor networks, control and automation technologies, and wearable gadgets. It is critical to regularly monitor the energy usage of the Internet of Things network since sensor nodes have limited power. In wireless sensor networks, the most significant obstacle is the exhaustion of available energy, and extending the network's lifetime can be accomplished by lowering the amount of energy that is spent. Energy aware routing protocol is highly important in IoT-based networks, although routing protocol that simply considers energy parameter has not performed successfully in managing excessive energy consumption. Energy aware routing protocol is very important in IoT-based network. The emergence of congestion in network nodes results in an increase in the amount of energy consumed and the loss of packets. Routing algorithms should strive for energy efficiency and load balancing across diverse nodes in order to lengthen the lifetime of a network. This will allow for more nodes to participate in the network. Clustering is one of the optimal techniques for efficient data aggregation among the sensor nodes. In a clustered setup, the Internet of Things (IoT) network is partitioned into a predetermined number of smaller networks. One of the most common and widely used clustering methods is LEACH, which stands for low-energy adaptive clustering hierarchy. It is unfortunate that it has some restrictions. In this study, we suggest the use of CAW-LEACH (CONGESTION AWARE - LEACH) as a means of enhancing energy efficiency, CH stability, and the capacity to aggregate data without experiencing congestion. The enhanced protocol that has been proposed takes into account both the depletion energy ratio (DE) and the expected remaining energy (PRE) of the nodes while selecting CH and generating random numbers. Its purpose is to ensure that the CH node that was just recently elected will not be given a second chance in this round. This technique establishes a correlation between the threshold that is utilised in conventional LEACH and each node's energy consumption ratio. The proposed congestion aware data aggregation scheme aggregates the data through traffic free paths by estimating the congestion indicator (CIN) & link error rate (LER), Residual Energy (RE) of the all-available routing paths. By comparing the suggested method to other energy-efficient data aggregation schemes, according to the findings of the experiments, the proposed technique increases the network's durability.