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Energy Aware Sensor Group Scheduling to Minimise Estimated Error from Noisy Sensor Measurements

  • Siddeswara Mayura Guru
  • Suhinthan Maheswararajah
Chapter
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Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 64)

Abstract

In wireless sensor network applications, sensor measurements are corrupted by noise resulting from harsh environmental conditions, hardware and transmission errors. Minimising the impact of noise in an energy constrained sensor network is a challenging task. We study the problem of estimating environmental phenomena (e.g., temperature, humidity, pressure) based on noisy sensor measurements to minimise the estimation error. An environmental phenomenon is modeled using linear Gaussian dynamics and the Kalman filtering technique is used for the state estimation. At each time step, a group of sensors is scheduled to transmit data to the base station to minimise the total estimated error for a given energy budget. We considered a diverse solution for scheduling sensors from heuristic-based Particle Swarm Optimisation (PSO) to dynamic programming and one-step-look-ahead methods. The simulation results show that PSO outperforms all other proposedmethods and it requires less computational time than dynamic programming.

Keywords

Root Mean Square Error Sensor Network Particle Swarm Optimisation Sensor Node Wireless Sensor Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Siddeswara Mayura Guru
    • 1
  • Suhinthan Maheswararajah
    • 2
  1. 1.CSIRO Tasmanian ICT CentreHobartAustralia
  2. 2.University of MelbourneParkvilleAustralia

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