Dynamic Localization Protocols for Mobile Sensor Networks

TL;DR

This paper introduces adaptive and predictive localization protocols for mobile sensor networks that balance energy consumption and accuracy by adjusting localization frequency based on sensor mobility.

Contribution

It proposes novel protocols that dynamically control localization frequency to reduce energy use while maintaining or improving accuracy in mobile sensor networks.

Findings

Protocols significantly reduce energy consumption.

Localization accuracy is maintained or improved.

Tradeoffs between energy and error are effectively managed.

Abstract

The ability of a sensor node to determine its physical location within a network (Localization) is of fundamental importance in sensor networks. Interpretating data from sensors will not be possible unless the context of the data is known; this is most often accomplished by tracking its physical location. Existing research has focused on localization in static sensor networks where localization is a one-time (or low frequency) activity. In contrast, this paper considers localization for mobile sensors: when sensors are mobile, localization must be invoked periodically to enable the sensors to track their location. The higher the frequency of localization, the lower the error introduced because of mobility. However, localization is a costly operation since it involves both communication and computation. In this paper, we propose and investigate adaptive and predictive protocols that control the frequency of localization based on sensor mobility behavior to reduce the energy requirements for localization while bounding the localization error. We show that such protocols can significantly reduce the localization energy without sacrificing accuracy (in fact, improving accuracy for most situations). Using simulation and analysis we explore the tradeoff between energy efficiency and localization error due to mobility for several protocols.