Papers
Topics
Authors
Recent
Search
2000 character limit reached

MAINT: Localization of Mobile Sensors with Energy Control

Published 10 Nov 2015 in cs.DC and cs.NI | (1511.03524v1)

Abstract: Localization is an important issue for Wireless Sensor Networks (WSN). A mobile sensor may change its position rapidly and thus require localization calls frequently. A localization may require network wide information and increase traffic over the network. It dissipates valuable energy for message communication. Thus localization is very costly. The control of the number of localization calls may save energy consumption, as it is rather expensive. To reduce the frequency of localization calls for a mobile sensor, we propose a technique that involves \textit{Mobility Aware Interpolation} (MAINT) for position estimation. It controls the number of localizations which gives much better result than the existing localization control schemes using mobility aware extrapolation. The proposed method involves very low arithmetic computation overheads. We find analytical expressions for the expected error in position estimation. A parameter, the time interval, has been introduced to externally control the energy dissipation. Simulation studies are carried out to compare the performances of the proposed method with some existing localization control schemes as well as the theoretical results. The simulation results shows that the expected error at any point of time may be computed from this expression. We have seen that constant error limit can be maintained increasing the time period of localization proportional to rate of change of direction of its motion. Increasing time period, the energy may be saved with a stable error limit.

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.