Arezoo Abasi and Hedieh Sajedi, University of Tehran, Iran

Wireless Sensor Networks (WSN) use a plurality of sensor nodes that unceasingly collected and sent data from a specific area to a base station. Cluster based data aggregation is one of the popular protocols in WSN. Clustering is an important procedure for extending the network lifetime in WSNs. Cluster Heads (CH) aggregate data from relevant cluster nodes and send it to the base station. A main challenge in WSNs is to select suitable CHs. In another communication protocol based on a tree construction, energy consumption is low because there are short paths between the sensors. In this paper, we propose Dynamic Fuzzy Clustering (DFC) data aggregation. The proposed method first uses fuzzy decision making approach for the selection of CHs and then a minimum spanning tree is constructed based on CHs. CHs are selected efficiently and accurately. The combining clustering and tree structure is reclaiming the advantages of the previous structures. Our method is compared to Low Energy Adaptive Clustering Hierarchy (LEACH), Cluster and Tree Dara Aggregation (CTDA), Modified Cluster based and Tree based Data Aggregation (MCTDA) and Cluster based and Tree based Power Efficient Data Collection and Aggregation (CTPEDCA).Our method decreases energy consumption of each node. In DFC data aggregation, the node lifetime is increased and the survival of the WSN is improved.

Wireless sensor networks; Data aggregation; Clustering; Minimum Spanning Tree; Fuzzy decision making.