Mobile sensor networks self localization based on multi-dimensional scaling

Abstract-In this paper, we define a mobile self-localization (MSL) problem for sparse mobile sensor networks, and propose an algorithm named Mobility Assisted MDS-MAP(P), based on Multi-dimensional Scaling (MDS) for solving the problem. For sparse sensor networks, all the existing localization algorithms fail to work properly due to the lack of distance or connectivity data to uniquely calculate the geo-locations. In MSL, we use mobile sensors to add extra distance constraints to a sparse network, by moving the mobile sensors in the area of deployment and recording distances to neighbors at some intermediate locations. MSL can also be used for localizing and tracking mobile objects in a robotic or body sensor network. Experiments and evaluations of the new algorithm are provided

Effective data routing using mobile sinks in disjoint mobile wireless sensor networks

In Mobile WSNs (MWSNs), disjoint clusters could be naturally formed in an unpredictable way that possess the nature of highly dynamic connected and disconnected schema. Many partitions of the network could happen in disjoint mobile wireless sensor networks (DMWSNs), and could last for a significant amount of time that can challenge current routing protocols in crisis-driven and geography-driven applications. We propose in this paper, two new centralized and distributed routing discovery protocols for DMWSN. In the centralized protocol, the static sink controls the motion of mobile sinks. In the distributed protocol, each mobile sink is responsible for collecting data in a specific region. In our work, the mobile sinks need to coordinate among themselves for communication with the base station (BS). The simulation results shows the advantage of our newly proposed protocols in terms of time delay, energy consumed, and the delivery ratio

Dynamic Localization of Multiple Mobile Subjects in Wireless Adhoc Networks

School of Electrical & Computer Engineerin