An energy-saving data aggregation method for wireless sensor networks based on the extraction of extrema points
Iman Dakhil Idan Saeedi, Ali Kadhum M. Al‐Qurabat
Abstract
The wireless sensor network (WSN) has been among the fast-growing areas in recent years in different fields, like health applications, military applications, the operations of disaster relief, etc. In an unattended, even hostile environment, nodes in WSNs are commonly deployed. What is worse, these nodes are fitted with minimal resources for communication, computation, storage and battery. It is also impossible to guarantee the lifespan of WSNs without reducing their network performance. A massive volume of application-specific data is produced by WSNs. Such data must be processed and sent to the base station by sensor nodes, which is an expensive matter. As the resources of sensor nodes are constrained, the key challenges facing WSNs are effective data processing and energy conservation. To tackle those challenges, data aggregation can be used, which is a popular approach that filters redundant data in-network and speeds up the extraction of knowledge. In this paper, we propose an energy-saving data aggregation method for WSNs based on the extraction of extrema points (DAEP) to greatly minimize the energy consumption of each node and boost the higher lifespan of WSN. The efficiency of the proposed method was measured by performing multiple simulation experiments based on real sensor readings collected in Intel Berkeley laboratories and comparing the results achieved with some work in the literature. The results show the ability of the proposed method to reduce the load on the sensor nodes in terms of reducing the amount of transmitted data by up to 69-80%, energy consumed by 73-77% while maintaining an acceptable level of accuracy compared to some existing works.