Thermal-Aware Sensor Scheduling for Distributed Estimation

  • Domenic Forte
  • Ankur Srivastava
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6131)


Recent work has shown that rising temperatures are increasing failures and reducing integrated circuit reliability. Although such results have prompted development of thermal management policies for stand-alone processors and on distributed power management, there is an overall lack of research on thermal management policies and their tradeoffs in sensor networks where sensors can overheat due to excessive sampling. Our primary focus in this paper is to examine the relationship between sampling, number of sensors, sensor node temperature, and state estimation error. We devise a scheduling algorithm which can achieve a desired real-time performance constraint while maintaining a thermal limit on temperature at all nodes in a network. Analytical results and experimentation are done for estimation with a Kalman filter for simplicity, but our main contributions should easily extend to any form of estimation with measurable error.


Sensor Network Sensor Node Kalman Filter Thermal Management Performance Constraint 
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

  • Domenic Forte
    • 1
  • Ankur Srivastava
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of MarylandCollege ParkMaryland

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