H-DHAC: A hybrid clustering protocol for Wireless Sensor Networks

Abstract

Clustering is one of the most energy-efficient methods to organize sensor nodes in Wireless Sensor Networks (WSNs). To perform clustering, location data are usually used for calculating the distance between sensor nodes. But location data may not always be available due to Global Positioning System (GPS) failures or may not be practical in consideration of cost. Alternatively, Received Signal Strength (RSS) or RSS Indicator (RSSI) is used as the distance estimator, but it has been showed that RSS or RSSI is unreliable in many studies. In order to mitigate these problems, we propose a hybrid clustering protocol - Hybrid Distributed Hierarchical Agglomerative Clustering (H-DHAC) - which uses both quantitative location data and binary qualitative connectivity data in clustering for WSNs. Our simulation results show that H-DHAC has a lower percentage of compromise in performance in terms of network life time and total transmitted data compared to similar approaches that use complete location data. However, H-DHAC still outperforms the well known clustering protocols, e.g., LEACH and LEACH-C.