Maximum Lifetime Target Coverage in Wireless Sensor Networks

Saadi, Nora; Bounceur, Ahcène; Euler, Reinhardt; Lounis, Massinissa; Bezoui, Madani; Kerkar, M.; Pottier, Bernard

doi:10.1007/s11277-019-06935-5

Cited by 21 publications

(8 citation statements)

References 23 publications

(33 reference statements)

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“…It is essential to consider a better network performance while designing the network deployment strategy with optimal coverage and connectivity [7]. The problem of the optimal coverage is formulated either as a greedy algorithm [8] or an integer optimization problem [9], which resembles the localization or placement problem of the facilities [10]. The sensor nodes' optimal numbers are computed using various methods like disk model, sector model, and geometry pattern model [11].…”

Section: Intelligent Systemmentioning

confidence: 99%

A Secure Communication Process of Wireless Sensor Network Architecture for Smart Urban Environment Monitoring Applications

Bhaskar¹,

Chakravarthi²

2021

IJACSA

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Wireless Sensor Network has been increasingly used for remote monitoring system and its adoption in increasing exponentially for larger application too. However, there are various challenges associated with both resource management and security that roots up when the deployment scale goes massive and distributed in order. The proposed system considers a case study of smart city management where the problems associated with data transmission and security has been addressed. This is carried out using the provisioning of urban environment monitoring system that is an essential system for smart city projects to assure the citizens' better-quality wellbeing. The scalable and effective urban environment monitoring system requires a seamless transmission of the data from the sensor nodes to the analytics engine. The existing architectures are more designed to suit very specifically the use-cases. As a contribution, the proposed system introduces a cost-effective architecture for environmental monitoring in urban zones of smart city named as a Smart Sensor Surveillance System (4S-UEM). The core idea of the proposed system is to offer a balance between resource efficiency and resilience secure communication in large scale deployment of WSN considering smart city as deployment and assessment area. The proposed system makes use of urban geographical clustering process in order to develop an organized structure of sensor nodes. Different from any existing studies, the proposed system introduces data analytical engine followed by secure routing using gateway. The design of the proposed system is carried out using layered architecture of the communication model targeting towards a cost-effective, energy optimal, and secure data transmission to the analytics engine.

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Section: Intelligent Systemmentioning

confidence: 99%

A Secure Communication Process of Wireless Sensor Network Architecture for Smart Urban Environment Monitoring Applications

Bhaskar¹,

Chakravarthi²

2021

IJACSA

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“…The same strategy was followed in [31], where a meta-heuristic was proposed to form a cover set for the target coverage problem. Saadi et al [32] proposed a maximum lifetime target coverage (MLTC) heuristic, which depends on minimally covered target (covered by least sensors). The proposed algorithm calculates the upper bound by observing such least covered targets and design subsets to monitor targets iteratively.…”

Section: A Target Full Coveragementioning

confidence: 99%

Proficient QoS-Based Target Coverage Problem in Wireless Sensor Networks

et al. 2020

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Assuring the coverage towards the predefined set of targets, power-constrained wireless sensor networks (WSNs) consist of sensing devices (i.e., sensor nodes) that are associated with limited battery life and fixed sensing range. All the sensors are collectively responsible for covering these sets of objects. The standard target coverage problem is the one where continuous coverage is provided over a predefined set of targets for the maximum possible duration so that the scarce resource (battery power) can be optimally utilized. Therefore, in order to incorporate quality of service (QoS) in the network and ensure smooth monitoring of the desired target set, the paper addresses target Q-Coverage, which is one of the variants of standard target coverage problem where a target is covered by at least Q-sensors (pre-defined number) in every cover set. A cover set is a subset of sensors which cover whole targets in a single iteration. In this paper, a greedy heuristic based technique, i.e., maximum coverage small lifetime (MCSL) has been proposed, which restricts the usages of those sensors that poorly cover targets and promotes the usage of those sensors that have maximum coverage and energy. Simulations are performed on static wireless sensor network with varying Q values to test the efficiency of the proposed method. The performance of the proposed heuristic is compared with optimal upper bound based on network lifetime, and results prove that performance is improvised by 94%. The obtained results are further compared with the existing approaches to prove the superiority of the proposed work via extensive experimentations.INDEX TERMS Coverage constraint, critical target, energy-efficient network, maximum coverage small lifetime, maximum lifetime target coverage, q-coverage.

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“…To enhance QoSensing in terms of coverage factor, many research works such as Coverage Contribution Area (CCA) [3], Centralized Lloyd-Like Algorithm (CLLA) [4], and the method to calculate the maximum lifetime target coverage MLTC [5] are presented in WSN. CCA resolves k-coverage problem in which at least k-nodes are required to cover the particular target.…”

Section: Introductionmentioning

confidence: 99%

4TQS: Four Tiers OVER Quality of Sensing with Energy Improvement in Wireless Sensor Network

Asqui¹,

Cedeño²

2021

IJCNS

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This paper presents four algorithms for QoSensing (4TQS) and routing on dynamics Wireless Sensor Networks. Since many types of researches held on QoSensing improvement in terms of coverage and connectivity enhancement. In a WSN with a density of 120 static and 30 mobile nodes, the major power-consuming activities are mobility and communication. Such power constraint has a great effect on the node activities and the same network. We analyzed the occurrence of coverage holes which is, regions inside the area of interest that are void of operational nodes for sensing and/or routing purposes. 4TQS method shows clustering phase through neuro-fuzzy based affinity propagation NFAP, sleep scheduling phase with ESLS algorithm and the assist of coverage enhancement phase in which HAHP is involved. Routing phase and connectivity metrics are improved with DTMR algorithm. Involvement of four efficient algorithms results in improved QoSensing in WSN. We analyzed our proposed method in both Star and Mesh topology in order to evaluate the QoSensing metrics in both topologies. Our method shows promising results in QoSensing metrics or performance in dynamics WSNs.

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Maximum Lifetime Target Coverage in Wireless Sensor Networks

Cited by 21 publications

References 23 publications

A Secure Communication Process of Wireless Sensor Network Architecture for Smart Urban Environment Monitoring Applications

A Secure Communication Process of Wireless Sensor Network Architecture for Smart Urban Environment Monitoring Applications

Proficient QoS-Based Target Coverage Problem in Wireless Sensor Networks

4TQS: Four Tiers OVER Quality of Sensing with Energy Improvement in Wireless Sensor Network

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