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Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks

Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks
Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks
Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the network’s energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of ‘virtual clusters,’ forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The ‘distributed formation’ algorithm automatically forms and classifies the virtual clusters. The ‘round robin sample scheme’ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption.
Wireless sensor networksSpatial correlationVirtual clusterEnergy balance
1687-1472
1-15
Li, Xun
393ace3b-1536-4e4f-ba57-436c63cf1c79
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
White, Neil M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Li, Xun
393ace3b-1536-4e4f-ba57-436c63cf1c79
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
White, Neil M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c

Li, Xun, Merrett, Geoff V. and White, Neil M. (2013) Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 2013 (230), 1-15. (doi:10.1186/1687-1499-2013-230).

Record type: Article

Abstract

Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the network’s energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of ‘virtual clusters,’ forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The ‘distributed formation’ algorithm automatically forms and classifies the virtual clusters. The ‘round robin sample scheme’ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption.

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More information

Submitted date: 19 January 2013
Accepted/In Press date: 15 August 2013
Published date: 14 September 2013
Additional Information: This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Wireless sensor networksSpatial correlationVirtual clusterEnergy balance
Organisations: Electronic & Software Systems, EEE

Identifiers

Local EPrints ID: 358051
URI: http://eprints.soton.ac.uk/id/eprint/358051
ISSN: 1687-1472
PURE UUID: 6517e6d3-51b4-4295-8260-18b0a5879a24
ORCID for Geoff V. Merrett: ORCID iD orcid.org/0000-0003-4980-3894
ORCID for Neil M. White: ORCID iD orcid.org/0000-0003-1532-6452

Catalogue record

Date deposited: 30 Sep 2013 07:57
Last modified: 15 Mar 2024 03:23

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Contributors

Author: Xun Li
Author: Geoff V. Merrett ORCID iD
Author: Neil M. White ORCID iD

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