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A MARKOV-MODULATED DIFFUSION MODEL FOR ENERGY HARVESTING SENSOR NODES

Published online by Cambridge University Press:  19 June 2017

Omer H. Abdelrahman Open the ORCID record for Omer H. Abdelrahman [Opens in a new window]
Omer H. Abdelrahman*
Affiliation:
Department of Electrical and Electronic Engineering, Intelligent Systems and Networks, Imperial College, London SW7 2BT, UK E-mail: o.abd06@imperial.ac.uk
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Abstract

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This paper presents a probability model of an energy-harvesting wireless sensor node, with the objective of linking quality of sensed data to energy consumption and self-sustainability. The model departs from the common energy discretization framework used in the literature, and instead uses a diffusion process modulated by discrete packet arrival and transmission processes for the detailed representation of renewable energy supply, consumption and storage. An analytical–numerical method is developed to compute the average time until the node experiences an outage, due to lack of energy, for a given workload and ambient energy characteristics, battery capacity and initial charge. The results are illustrated with numerical examples.

Keywords

energy depletionenergy harvestingdiffusion processfirst-passage timeinternet of thingsself-sustainability

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 31 , Special Issue 4: G-Networks and their Applications , October 2017 , pp. 505 - 515
Copyright
Copyright © Cambridge University Press 2017 

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