scholarly journals A Reinforcement Learning-Based ToD Provisioning Dynamic Power Management for Sustainable Operation of Energy Harvesting Wireless Sensor Node

2014 ◽  
Vol 2 (2) ◽  
pp. 181-191 ◽  
Author(s):  
Roy Chaoming Hsu ◽  
Cheng-Ting Liu ◽  
Hao-Li Wang
2021 ◽  
Vol 20 ◽  
pp. 57-67
Author(s):  
Rakhee Kallimani ◽  
Sridhar Iyer

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.


2012 ◽  
Vol 29 (2) ◽  
pp. 76-82 ◽  
Author(s):  
Kah‐Yoong Chan ◽  
Hee‐Joe Phoon ◽  
Chee‐Pun Ooi ◽  
Wai‐Leong Pang ◽  
Sew‐Kin Wong

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