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Communication Dans Un Congrès Année : 2014

An Emulation-Based Method for Lifetime Estimation of Wireless Sensor Networks

Wilfried Dron
  • Fonction : Auteur
  • PersonId : 971361
Simon Duquennoy
  • Fonction : Auteur
Thiemo Voigt
  • Fonction : Auteur
Khalil Hachicha
  • Fonction : Auteur
  • PersonId : 970180
  • IdRef : 110125401
Patrick Garda
  • Fonction : Auteur
  • PersonId : 970182

Résumé

Lifetime estimation in Wireless Sensor Networks (WSN) is crucial to ensure that the network will last long enough (low maintenance cost) while not being over-dimensioned (low initial cost). Existing solutions have at least one of the two following limitations: (1) they are based on theoretical models or high-level protocol implementations, overlooking low-level (e.g., hardware, driver, etc.) constraints which we find have a significant impact on lifetime, and (2) they use an ideal battery model which over-estimates lifetime due to its constant voltage and its inability to model the non-linear properties of real batteries. We introduce a method for WSN lifetime estimation that operates on compiled firmware images and models the complex behavior of batteries. We use the MSPSim/Cooja node emulator and network simulator to run the application in a cycle-accurate manner and log all component states. We then feed the log into our lifetime estimation framework, which models the nodes and their batteries based on both technical and experimental specifications. In a case study of a Contiki RPL/6LoWPAN application, we identify and resolve several low-level implementation issues, thereby increasing the predicted network lifetime from 134 to 484 days. We compare our battery model to the ideal battery model and to the lifetime estimation based on the radio duty cycle, and find that there is an average over-estimation of 36% and 76% respectively.

Dates et versions

hal-01211777 , version 1 (05-10-2015)

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Citer

Wilfried Dron, Simon Duquennoy, Thiemo Voigt, Khalil Hachicha, Patrick Garda. An Emulation-Based Method for Lifetime Estimation of Wireless Sensor Networks. IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), 2014, May 2014, Marina Del Ray, Californie, United States. pp.241-248, ⟨10.1109/DCOSS.2014.10⟩. ⟨hal-01211777⟩
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