Energy Efficient Data Aggregation and Density-Based Spatial Clustering of Applications with Noise for Activity Monitoring in Wireless Sensor Networks
Jainendra Singh, Zaheerud din · Engineered Science · 2022
Clustering saves energy and extends network longevity in applications such as activity monitoring in wireless sensor networks.Clustering separate tes nodes into clusters from which the cluster head can collect and send data to the base station.The current investigation also demonstrates data aggregation at the cluster head before sending it to the base station.The cluster head is chosen based on leftover energy and distance from the sink and other network nodes.The current study found that the existing clustering protocol decays its energy quickly, but our proposal can overcome these challenges and sensors can survive longer.This paper proposes Density-based Spatial Clustering of Applications with Noise (DB-SCAN) clustering algorithms to make data gathering and transmitting of data energy efficient.The data aggregation protocol will collect the packets and combine them.Further, it will be forwarded using the clustering approach.It is used to improve transmission efficiency by reducing the transmission of redundant data to the sink.This proposed protocol, Energy Efficient Cluster based Data Aggregation (EECDA), will help increase network lifetime by ensuring uniform distribution of energy amongst the nodes.