Adaptive Duty Cycling in Sensor Networks via Continuous Time Markov Chain Modelling

• Main Authors: Chan, Ronald Wai Hong, Zhang, Pengfei, Zhang, Wenyu, Nevat, Ido, VALERA, Alvin Cerdena, TAN, Hwee Xian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Computer Sciences; Databases and Information Systems; Digital Communications and Networking
• Online Access: https://ink.library.smu.edu.sg/sis_research/3167
• Institution: Singapore Management University

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.