An Efficient Data Aggregation Approach for Large Scale Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) have significant potential in many application domains such as agriculture, health, environmental monitoring, battlefield surveillance, and wild fire detection. They, however cannot be used in large geographical areas due to the short communication range of sensors.. In addition, sensor networks have been the lack of available network management and control tools, such as for determining the degree of data aggregation prior to transforming it into useful information. Designing different network management tools such for routing, localization, and data aggregation are, therefore, required in large scale WSNs. Only a few of the existing data aggregation methods have been developed for a large scale WSN. In this paper, we propose an efficient data aggregation scheme for large scale WSNs that considers the tradeoff between energy efficiency and end-to-end delay. Simulation results show that the proposed scheme has better performance than an existing standard data aggregation approach, namely SUMAC.