A Data Gathering Algorithm for a Mobile Sink in Large-Scale Sensor Networks

Abstract

Sink mobility is one of the most comprehensive trends for information gathering in sensor networks. This way of information gathering has a prominent role in balancing the energy consumption among sensor networks, and culling the hotspots problem of sensor networks. In this paper, a well planned adaptive moving strategy for a mobile sink in large-scale, hierarchical sensor networks is presented. The mobile sink traverses the entire network uploading the sensed data from cluster heads in time driven scenarios. The mobile sink trajectory is planned such that all heads require no multi-hop relays to reach the mobile sink. The proposed system aims at extending the lifetime of the sensor network by achieving a high level of energy efficiency and fair balancing of energy consumption across all network heads. Furthermore, reducing the loss that data incur due to buffer overflow. Extensive simulations are conducted in order to validate the proposed strategy. The adopted data gathering scheme outperforms the static sink scheme and periphery scheme in terms of life time elongation, and scalability.