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Sensors 2018, 18(3), 689;

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments

Computer Science Department, State University of Piaui, Rua Joao Cabral, 2231-Piraja, 64002-150 Teresina, Piaui, Brazil
Graduate Program in Applied Informatics (PPGIA), University of Fortaleza, Av. Washington Soares, 1321-Edson Queiroz, 60811-905 Fortaleza, Ceará, Brazil
Graduate Program in Compupter Science (PPGCC), Federal University of Piaui, Ministro Petronio Portela Campus, 64049-550 Teresina, Piaui, Brazil
Author to whom correspondence should be addressed.
Received: 7 January 2018 / Revised: 17 February 2018 / Accepted: 23 February 2018 / Published: 26 February 2018
(This article belongs to the Section Sensor Networks)
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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. View Full-Text
Keywords: ant colony optimization; clustering; virtualization; wireless sensor networks ant colony optimization; clustering; virtualization; wireless sensor networks

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Lemos, M.V.S.; Filho, R.H.; Rabêlo, R.A.L.; de Carvalho, C.G.N.; Mendes, D.L.S.; Costa, V.G. An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments. Sensors 2018, 18, 689.

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