Data Research, Vol. 2, Issue 3, Jun  2018, Pages 88-96; DOI: 10.31058/j.data.2018.23004 10.31058/j.data.2018.23004

A Comprehensive Model for Energy Consumption in Wireless Sensor Networks Using the Markov Model

Data Research, Vol. 2, Issue 3, Jun  2018, Pages 88-96.

DOI: 10.31058/j.data.2018.23004

Seyyedjalaleddin Dastgheib 1 , Farzaneh Fekrisafarizadeh 2*

1 Department of Computer Engineering, Shiraz University, Shiraz, Iran

2 Department of Computer Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran

Received: 8 July 2018; Accepted: 24 August 2018; Published: 16 October 2018

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Abstract

Due to the availability of energy-efficient sensors, microprocessors, and radio frequency circuits for data transfer, wireless sensor networks developed rapidly and spread. Wireless sensor networks that include thousands of low-cost sensor nodes are used in various applications such as health surveillance, battlefield surveillance, and environmental monitoring. The sensor node non-rechargeable, non-replaceable and limited power supply is considered as the main challenges of these type of networks. With the completion of the nodes power supply, the node actually remains unused. Sleep-wake scheduling is used to reduce energy consumption and extend the life of nodes. In this paper we try to investigate sleep-wake scheduling in sensor nodes with the Markov model. In probability theory, a Markov model is a stochastic model used to model randomly changing systems where it is assumed that future states depend only on the current state not on the events that occurred before it (that is, it assumes the Markov property). Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable. For this reason, in the fields of predictive modeling and probabilistic forecasting, it is desirable for a given model to exhibit the Markov property. It is expected that the proposed Markov model covers all aspects of sleep/wake scheduling in wireless sensor networks.

Keywords

Wireless Sensor Network, Markov Model, Scheduling, Sleep/Awake

Copyright

© 2017 by the authors. Licensee International Technology and Science Press Limited. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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