Discovering the location of the mobile nodes carried by people is important issue for many sensor applications. Several localization techniques have been proposed, but human mobility patterns and collaboration between mobile nodes have been seldom considered. In this paper, we propose a mobile node localization system based on collaboration and route information that characterizes human mobility. To validate the feasibility of our approach, the proposed system is implemented and experiments are conducted on real routes and to evaluate various scenarios, simulation experiment was also conducted.

One interesting issue in recent sensor network research is the application of sensor nodes to mobile objects, such as people or animals, to gather non-stationary information. Apparently, locating mobile nodes is essential in many of the mobile sensor applications. Although several localization techniques have been proposed to locate mobile nodes, the mechanisms are usually based on many impractical assumptions, and mobility pattern of the mobile object is seldom considered. In this paper, we propose a practical and yet simple mobile node localization system using nearby anchor information which contains absolute time and positions. A history of anchor information is used to characterize the mobility of mobile devices. The unknown node then calculates its position with the archived anchor using a regression model. The simulation results show that the proposed algorithm outperforms previous methods under realistic conditions. We have also implemented the algorithm on real hardware, and diverse experiments were conducted to validate the feasibility of the proposed approach.

Previous work for maximizing system lifetime in sensor networks has proposed mechanism such on clustered networks or energy-aware routing protocols. In those works, prediction of lifetime and measurement of energy are dependent on predefined data such as transmission energy, data rate and so on. In common sensor networks, packets are unevenly generated and transmission energy is difficult to measure. Previous work cannot reflect the attributes of real networks. In this paper, we propose a routing algorithm that considers hardware-dependent battery consumption behavior of underlying sensor hardware. Each node reads its current voltage level and estimates its lifetime. Routing is then decided upon the predicted lifetime. Simulation results show that the proposed protocol extends the network lifetime by more than 12% over traditional methods.