Linear WSN lifetime maximization for pipeline monitoring using hybrid K-means ACO clustering algorithm Abdelhafidh, Maroua Fourati, Mohamed Fourati, Lamia Chaari Mnaouer, Adel Ben Zid, Mokhtar 2020-01-29T09:13:56Z 2020-01-29T09:13:56Z 2018 en_US 2018
dc.description This conference paper is not available at CUD collection. The version of scholarly record of this conference paper is published in 2018 Wireless Days (WD) (2018), available online at: en_US
dc.description.abstract Water Pipeline Monitoring Systems have emerged as a reliable solution to maintain the integrity of the water distribution infrastructure. Various emerging technologies such as the Internet of Things, Physical Cyber Systems, and machine-to-machine networks are efficiently deployed to build a Structural Health Monitoring of pipeline and invoke the deployment of the Industrial Wireless Sensor Networks (IWSN) technology. Efficient energy consumption is imperatively required to maintain the continuity of the network and to allow an adequate interconnection between sensor nodes deployed in the harsh environment. In this context, to maximize the Lifetime of the WSN under Water Distribution system domain is a primordial objective to ensure its permanently working and to enable a promising solution for hydraulic damage detection according to diverse performance metrics. In this paper, we propose an hybrid clustering algorithm based on K-means and Ant Colony Optimization (ACO); called K-ACO to improve the WSN Lifetime. © 2018 IEEE. en_US
dc.identifier.citation Abdelhafidh, M., Fourati, M., Fourati, L. C., Mnaouer, A. B., & Zid, M. (2018). Linear WSN lifetime maximization for pipeline monitoring using hybrid K-means ACO clustering algorithm. In IFIP Wireless Days (Vol. 2018–April, pp. 178–180). en_US
dc.identifier.isbn 9781538656327
dc.identifier.issn 21569711
dc.language.iso en en_US
dc.publisher IEEE Computer Society en_US
dc.relation Authors Affiliations: Abdelhafidh, M., Digital Research Center of Sfax (CRNS), Tunisia, National Engineering School of Sfax, University of Sfax, Tunisia; Fourati, M., Digital Research Center of Sfax (CRNS), Tunisia; Fourati, L.C., Digital Research Center of Sfax (CRNS), Tunisia; Mnaouer, A.B., Canadian University of Dubai (CUD), United Arab Emirates; Zid, M., Research Direction of Tunisian Chemical Group, Gafsa, Tunisia
dc.relation.ispartofseries IFIP Wireless Days;2018-April
dc.rights Permission to reuse abstract has been secured from Institute of Electrical and Electronics Engineers Inc.
dc.rights.holder Copyright : 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.subject Ant colony optimization en_US
dc.subject Industrial wireless sensor network en_US
dc.subject K-means en_US
dc.subject Network Lifetime (NL) en_US
dc.subject Water Pipeline monitoring en_US
dc.subject Artificial intelligence en_US
dc.subject Damage detection en_US
dc.subject Energy utilization en_US
dc.subject Hydraulic machinery en_US
dc.subject Machine-to-machine communication en_US
dc.subject Pipelines en_US
dc.subject Sensor nodes en_US
dc.subject Structural health monitoring (SHM) en_US
dc.subject Water distribution systems en_US
dc.title Linear WSN lifetime maximization for pipeline monitoring using hybrid K-means ACO clustering algorithm en_US
dc.type Conference Paper en_US
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