Adaptive duty cycling in sensor networks via Continuous Time Markov Chain modelling

Ronald Chan, Pengfei Zhang, Wenyu Zhang, Ido Nevat, Alvin Valera, Hwee Xian Tan, Natarajan Gautam

Research output: Chapter in Book/Entry/PoemConference contribution

8 Scopus citations


The dynamic and unpredictable nature of energy harvesting sources that are used in wireless sensor networks necessitates the need for adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve energy-neutrality, whereby both energy supply and demand are balanced. This paper proposes a framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the operating duty cycle of the node, and application-level QoS requirements. We model the system as a Continuous Time Markov Chain (CTMC), and derive analytical expressions for key QoS metrics - such as latency, loss probability and power consumption. We then formulate and solve the optimal operating duty cycle as a non-linear optimization problem, using latency and loss probability as the constraints. Simulation results show that a Markovian duty cycling scheme can outperform periodic duty cycling schemes.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Communications, ICC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781467364324
StatePublished - Sep 9 2015
Externally publishedYes
EventIEEE International Conference on Communications, ICC 2015 - London, United Kingdom
Duration: Jun 8 2015Jun 12 2015

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607


OtherIEEE International Conference on Communications, ICC 2015
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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