Browsing by Author "Zid, Mokhtar"
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Item Lifetime maximization for pipeline monitoring based on data aggregation and bio-inspired clustering algorithm(Institute of Electrical and Electronics Engineers Inc., 2018) Abdelhafidh, Maroua; Fourati, Mohamed; Fourati, Lamia Chaari; Mnaouer, Adel Ben; Zid, MokhtarHydraulic 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.Item Linear WSN lifetime maximization for pipeline monitoring using hybrid K-means ACO clustering algorithm(IEEE Computer Society, 2018) Abdelhafidh, Maroua; Fourati, Mohamed; Fourati, Lamia Chaari; Mnaouer, Adel Ben; Zid, MokhtarWater 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.Item Novel data preprocessing algorithm for WSN lifetime maximization in water pipeline monitoring system(Institute of Electrical and Electronics Engineers Inc., 2019) Abdelhafidh, Maroua; Fourati, Mohamed; Fourati, Lamia Chaari; Mnaouer, Adel Ben; Zid, MokhtarWireless Sensor Networks (WSN) are widely deployed to maintain Structural Health Monitoring of Water Pipeline System (WPS). Accordingly, it is imperatively important to ensure reliable communication between sensor nodes deployed in harsh environment to allow a continuous data collection and processing. In this context, we propose and implement an energy efficient solution that enables a seamless interconnection between sensor nodes, and trusty data transmission in order to maximize the network lifetime. After a clustering step, a Data Redundancy Elimination technique is applied to remove redundant data at each cluster head. This operation is followed by a data fusion algorithm based on Dempster-Shafer evidence theory at the Base Station. This scheme is proposed with aim of reducing the size of data carried by the network and consequently save on energy consumption. This results in improved WSN lifetime and more accurate WPS systems. © 2019 IEEE.