Energy-Efficient Routing and Data Aggregation in Sensor Networks: An Experimental Study

Several sensor network applications, such as environmental monitoring, require data aggregation to an observer (e.g., a base station). For this purpose, a data aggregation tree rooted at the observer is constructed in the network to reduce communication overhead and facilitate faster and more reliable results. Node clustering can be employed for this purpose, to further balance load among sensor nodes and prolong the network lifetime. In this paper, we design and implement a system, iHEED, in which node clustering is integrated with multi-hop routing for TinyOS. In iHEED, sensor nodes are clustered prior to constructing the data aggregation tree. We consider simple data aggregation operators, such as AVG or MAX. We perform experiments on a sensor network testbed to quantify the benefits of integrating hierarchical routing with data aggregation. Our results indicate that, by using reduced intra-cluster transmission power and exploiting intra-cluster and inter-cluster data aggregation, network lifetime is prolonged by a factor of 2 to 4, and successful transmissions are almost doubled. The overhead of the clustering process is subsumed by tree construction and maintenance overhead. Index Temlssensor networks, implementation, clustering, energy efficiency