Lifetime maximization for pipeline monitoring based on data aggregation and bio-inspired clustering algorithm

Date
2018
Authors
Abdelhafidh, Maroua
Fourati, Mohamed
Fourati, Lamia Chaari
Mnaouer, Adel Ben
Zid, Mokhtar
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Hydraulic failures in Water Pipeline System (WPS) can cause catastrophic environmental hazards. Wireless Sensor Networks (WSN) are greatly deployed to maintain a Structural Health Monitoring of pipeline and supervise the WPS. Since, its implementation increases significantly, its energy consumption represents a critical challenge that should be imperatively investigated in order to ensure an efficient and seamless interconnection between sensor nodes. In this context, the data aggregation techniques are well-designed and various smart algorithms are developed to reduce the quantity of transmitted data and to minimize the energy consumption. In this paper, we combine between data aggregation and bio-inspired clustering algorithm in order to improve the WSN Lifetime. © 2018 IEEE.
Description
This conference paper is not available at CUD collection. The version of scholarly record of this conference paper is published in 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC) (2018), available online at: https://doi.org/10.1109/IWCMC.2018.8450302.
Keywords
Batteries, Clustering algorithms, Data aggregation, Energy consumption, Monitoring, Pipelines, Wireless sensor networks (WSN), Energy utilization, Mobile computing, Sensor nodes, Solar cells, Structural health monitoring (SHM), Water pipelines, Wireless telecommunication systems, Critical challenges, Data aggregation, Environmental hazards, Hydraulic failure, Lifetime maximization, Pipe-line systems, Pipeline monitoring, Smart algorithms, Clustering algorithms
Citation
Abdelhafidh, M., Fourati, M., Fourati, L. C., Ben Mnaouer, A., & Zid, M. (2018). Lifetime maximization for pipeline monitoring based on data aggregation and bio-inspired clustering algorithm. In 2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018 (pp. 666–671). https://doi.org/10.1109/IWCMC.2018.8450302