Mobility-aware hierarchical clustering in mobile wireless sensor networks

Abstract

Wireless sensor networks (WSNs) are one of the chief enabling technologies for the Internet of Things. These networks are severely resource-constrained which calls for designing energy-efficient and effective routing techniques. The hierarchical- or clustering-based routing approaches have shown to improve both energy-efficiency and scalability in WSNs. However, when clustering is implemented in mobile WSNs (MWSNs), the mobility of sensor nodes results in high data loss due to possible dis-association of nodes with their cluster heads which negatively affects the data rates and energy consumption. In order to mitigate the impact of node mobility on clustering, we propose two mobility-aware hierarchical clustering algorithms for MWSN based on three-layer clustering hierarchy: mobility-aware centralized clustering algorithm (MCCA) and mobility-aware hybrid clustering algorithm (MHCA). The MCCA algorithm employs centralized gridding at both layers of clustering hierarchy, and the MHCA algorithm employs centralized gridding at the upper layer and distributed clustering at the lower layer. The simulation results show that our proposed algorithms improve network lifetime, reduce energy consumption, stabilize cluster formation, and enhance data rates in mobile sensor networks. We also observe that the centralized clustering approach is superior to the hybrid clustering approach.