An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments
Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user’s queries or applications. Recent works perform provisioning by clustering sensor nodes b...
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doaj-e7755aabc60f46229c05806c5bf6b7c72020-11-24T20:48:16ZengMDPI AGSensors1424-82202018-02-0118368910.3390/s18030689s18030689An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds EnvironmentsMarcus Vinícius de S. Lemos0Raimir Holanda Filho1Ricardo de Andrade L. Rabêlo2Carlos Giovanni N. de Carvalho3Douglas Lopes de S. Mendes4Valney da Gama Costa5Computer Science Department, State University of Piaui, Rua Joao Cabral, 2231-Piraja, 64002-150 Teresina, Piaui, BrazilGraduate Program in Applied Informatics (PPGIA), University of Fortaleza, Av. Washington Soares, 1321-Edson Queiroz, 60811-905 Fortaleza, Ceará, BrazilGraduate Program in Compupter Science (PPGCC), Federal University of Piaui, Ministro Petronio Portela Campus, 64049-550 Teresina, Piaui, BrazilComputer Science Department, State University of Piaui, Rua Joao Cabral, 2231-Piraja, 64002-150 Teresina, Piaui, BrazilGraduate Program in Compupter Science (PPGCC), Federal University of Piaui, Ministro Petronio Portela Campus, 64049-550 Teresina, Piaui, BrazilComputer Science Department, State University of Piaui, Rua Joao Cabral, 2231-Piraja, 64002-150 Teresina, Piaui, BrazilVirtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user’s queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user’s queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios.http://www.mdpi.com/1424-8220/18/3/689ant colony optimizationclusteringvirtualizationwireless sensor networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Marcus Vinícius de S. Lemos Raimir Holanda Filho Ricardo de Andrade L. Rabêlo Carlos Giovanni N. de Carvalho Douglas Lopes de S. Mendes Valney da Gama Costa |
spellingShingle |
Marcus Vinícius de S. Lemos Raimir Holanda Filho Ricardo de Andrade L. Rabêlo Carlos Giovanni N. de Carvalho Douglas Lopes de S. Mendes Valney da Gama Costa An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments Sensors ant colony optimization clustering virtualization wireless sensor networks |
author_facet |
Marcus Vinícius de S. Lemos Raimir Holanda Filho Ricardo de Andrade L. Rabêlo Carlos Giovanni N. de Carvalho Douglas Lopes de S. Mendes Valney da Gama Costa |
author_sort |
Marcus Vinícius de S. Lemos |
title |
An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments |
title_short |
An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments |
title_full |
An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments |
title_fullStr |
An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments |
title_full_unstemmed |
An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments |
title_sort |
energy-efficient approach to enhance virtual sensors provisioning in sensor clouds environments |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-02-01 |
description |
Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user’s queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user’s queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios. |
topic |
ant colony optimization clustering virtualization wireless sensor networks |
url |
http://www.mdpi.com/1424-8220/18/3/689 |
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