A distributed navigation strategy for mobile sensor networks with the probabilistic wireless links

Aqeel Madhag, Jongeun Choi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Mobile sensor networks have been widely used to predict the spatio-temporal physical phenomena for various scientific and engineering applications. To accommodate the realistic models of mobile sensor networks, we incorporated probabilistic wireless communication links based on packet reception ratio (PRR) with distributed navigation. We then derived models of mobile sensor networks that predict Gaussian random fields from noise-corrupted observations under probabilistic wireless communication links. For the given model with probabilistic wireless communication links, we derived the prediction error variances for further sampling locations. Moreover, we designed a distributed navigation that minimizes the network cost function formulated in terms of the derived prediction error variances. Further, we have shown that the solution of distributed navigation with the probabilistic wireless communication links for mobile sensor networks are uniformly ultimately bounded with respect to that of the distributed one with the R-disk communication model. According to Monte Carlo simulation results, agent trajectories under distributed navigation with the probabilistic wireless communication links are similar to those with the R-disk communication model, which confirming the theoretical analysis.

Original languageEnglish
Article number031004
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume139
Issue number3
DOIs
Publication statusPublished - 2017 Mar 1

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wireless communication
navigation
Sensor networks
Telecommunication links
Wireless networks
Navigation
sensors
communication
Communication
predictions
Cost functions
sampling
Trajectories
trajectories
engineering
Sampling
costs
simulation

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

Cite this

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