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dc.contributor.author
Riva, Guillermo Gaston
dc.contributor.author
Finochietto, Jorge Manuel
dc.date.available
2019-07-16T13:38:39Z
dc.date.issued
2012-12
dc.identifier.citation
Riva, Guillermo Gaston; Finochietto, Jorge Manuel; Pheromone-based In-Network Processing for wireless sensor network monitoring systems; Macrothink Institute; Network Protocols and Algorithms; 4; 4; 12-2012; 156-173
dc.identifier.issn
1943-3581
dc.identifier.uri
http://hdl.handle.net/11336/79616
dc.description.abstract
Monitoring spatio-temporal continuous fields using wireless sensor networks (WSNs) has emerged as a novel solution. An efficient data-driven routing mechanism for sensor querying and information gathering in large-scale WSNs is a challenging problem. In particular, we consider the case of how to query the sensor network information with the minimum energy cost in scenarios where a small subset of sensor nodes has relevant readings. In order to deal with this problem, we propose a Pheromone-based In-Network Processing (PhINP) mechanism. The proposal takes advantages of both a pheromone-based iterative strategy to direct queries towards nodes with relevant information and query- and response-based in-network filtering to reduce the number of active nodes. Additionally, we apply reinforcement learning to improve the performance. The main contribution of this work is the proposal of a simple and efficient mechanism for information discovery and gathering. It can reduce the messages exchanged in the network, by allowing some error, in order to maximize the network lifetime. We demonstrate by extensive simulations that using PhINP mechanism the query dissemination cost can be reduced by approximately 60% over flooding, with an error below 1%, applying the same in-network filtering strategy.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Macrothink Institute
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Bio-Inspired Networking
dc.subject
Computational Intelligence
dc.subject
In-Network Filtering
dc.subject
Monitoring Systems
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Routing Algorithms And Protocols
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Swarm Intelligence
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Wireless Sensor Networks
dc.subject.classification
Ingeniería de Sistemas y Comunicaciones
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Pheromone-based In-Network Processing for wireless sensor network monitoring systems
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-07-15T20:43:17Z
dc.journal.volume
4
dc.journal.number
4
dc.journal.pagination
156-173
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Las Vegas
dc.description.fil
Fil: Riva, Guillermo Gaston. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Universidad Tecnológica Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
dc.description.fil
Fil: Finochietto, Jorge Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Estudios Avanzados en Ingeniería y Tecnología. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Estudios Avanzados en Ingeniería y Tecnología; Argentina
dc.journal.title
Network Protocols and Algorithms
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.5296/npa.v4i4.2206
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