A Location Prediction Based Data Gathering Protocol for Wireless Sensor Networks Using a Mobile Sink

Abstract

Abstract. Traditional data gathering protocols in wireless sensor networks are mainly based on static sink, and data are routed in a multi-hop manner towards sink. In this paper, we proposed a location predictable data gathering protocol with a mobile sink. A sink's location prediction principle based on loose time synchronization is introduced. By calculating the mobile sink location information, every source node in the network is able to route data packets timely to the mobile sink through multi-hop relay. This study also suggests a dwelling time dynamic adjustment method, which takes the situation that different areas may generate different amount of data into account, resulting in a balanced energy consumption among nodes. Simulation results show that our data gathering protocol enables data routing with less data transmitting time delay and balance energy consumption among nodes.

A Location Prediction Algorithm with Daily Routines in Location-Based Participatory Sensing Systems

“…Except for the Markov model and HMM, there are some other location prediction algorithms that are used to analyze location information in literature [18–26], such as the artificial neural network-based algorithm [18], Bayesian network-based methods [19, 20], mobile-sink-based methods [21, 22], the regression-based method [23], and mobile anchor assisted localization algorithms [24, 25]. These methods predict future positions of nodes from different perspectives, which focus on the behavior of each single node.…”