Open AccessDynamic Power Management Model for a Wireless Sensor Node
Author(s) -
Rakhee Kallimani,
Sridhar Iyer
Publication year - 2021
Publication title -
proceedings of engineering and technology innovation
Language(s) - English
Resource type - Journals
eISSN - 2518-833X
pISSN - 2413-7146
DOI - 10.46604/peti.2021.8455
Subject(s) - node (physics) , fifo (computing and electronics) , wireless sensor network , computer science , queue , real time computing , event (particle physics) , energy consumption , computer network , power management , power (physics) , sensor node , queueing theory , markov chain , key distribution in wireless sensor networks , wireless , wireless network , engineering , telecommunications , electrical engineering , physics , structural engineering , quantum mechanics , computer hardware , machine learning
Dynamic power management (DPM) is an efficient technique to design low-power and energy-efficient nodes for wireless sensor networks. This article demonstrates the stochastic behaviour of an input event arrival which is modelled with first-in first-out (FIFO) queue and a single server. An event-driven sensor node is developed based on semi-Markov model. The article investigates the factors affecting the performance of the individual sensor node with detailed analysis considering power consumption and lifetime to be the performance metrics under study. The results demonstrate the impact of the change in event arrival and the probability of change detection on the performance of the node. It is observed that (i) the number of generated events increases with the change in the average value of the distribution which affects the service time in turn resulting in a variation of the server utilization, and that (ii) the increase in the detection probability increases the power consumption decreasing the lifetime of the node.