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

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

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 Q...

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Bibliographic Details
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
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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