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Redundancy estimation and adaptive density control inwireless sensor networks

Title	Redundancy estimation and adaptive density control inwireless sensor networks
Author	Machado, R., He, H., Wang, G., Tekinay, Şirin
Publication Date:	2010
Publication Place	- Old City Publishing
Subject	Wireless sensor networks, Redundancy estimation, Environment variation, Neural networks
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	2-s2.0-78651467532
Record ID	d5573a3a-1854-405d-86cb-d5208c3bbe7c
Library Location	Electrical & Electronics Engineering
Date	2010
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	While dense random deployment satisfies coverage and sensing requirements, constructing dense networks of sensor nodes poses the problems of obtaining node location information.We provide an analytical framework for estimating the redundancy in a single-hop WSN of random deployment of nodes without the need of location information of nodes. We use an information theoretic approach to estimate the redundancy and provide the Cramer-Rao bound on the error in the estimation. We illustrate this redundancy estimation approach and calculate the bounds on the error in the estimation for a WSN with 1-redundancy. We also analytically show the inter-dependence between redundancy and network lifetime for random deployment. We further study the energy model of a WSN as interdependence between the environmental variation and its impact on the energy consumption at individual nodes. Defining network energy as the sum of residual battery energy at nodes, we provide an analytical framework for the dependence of node energy and sensitivity of network energy as a function of environmental variation and reliability parameters. Using a neural network based approach, we perform adaptive density control and show how reliability requirements and environment variation influences the rate of change of network energy.
Cilt	10

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Redundancy estimation and adaptive density control inwireless sensor networks

Author Machado, R., He, H., Wang, G., Tekinay, Şirin

Publication Date 2010

Publication Place - Old City Publishing

Subject Wireless sensor networks, Redundancy estimation, Environment variation, Neural networks

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 2-s2.0-78651467532

Record ID d5573a3a-1854-405d-86cb-d5208c3bbe7c

Library Location Electrical & Electronics Engineering

Date 2010

Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Sample Text While dense random deployment satisfies coverage and sensing requirements, constructing dense networks of sensor nodes poses the problems of obtaining node location information.We provide an analytical framework for estimating the redundancy in a single-hop WSN of random deployment of nodes without the need of location information of nodes. We use an information theoretic approach to estimate the redundancy and provide the Cramer-Rao bound on the error in the estimation. We illustrate this redundancy estimation approach and calculate the bounds on the error in the estimation for a WSN with 1-redundancy. We also analytically show the inter-dependence between redundancy and network lifetime for random deployment. We further study the energy model of a WSN as interdependence between the environmental variation and its impact on the energy consumption at individual nodes. Defining network energy as the sum of residual battery energy at nodes, we provide an analytical framework for the dependence of node energy and sensitivity of network energy as a function of environmental variation and reliability parameters. Using a neural network based approach, we perform adaptive density control and show how reliability requirements and environment variation influences the rate of change of network energy.

Cilt 10