Multi-Objective WSN Deployment Using Genetic Algorithms Under Cost, Coverage, and Connectivity Constraints

Benatia, Mohamed Amin; Sahnoun, M’hammed; Baudry, David; Louis, Anne; Hami, Abdelkhalak El; Mazari, B.

doi:10.1007/s11277-017-3974-0

Cited by 68 publications

(58 citation statements)

References 35 publications

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“…The researchers in [4] designed a set of patterns to achieve k-connectivity (k ≤4) and full coverage, which proved optimal under any value of the ratio of the communication range (Rc) to the sensing range (Rs) among regular lattice deployment patterns. A multiobjective wireless sensor network (WSN) planning strategy based on evolutionary algorithms was proposed in [5]. In [6], the authors proposed that a long belt be divided into a few subbelts.…”

Section: Node Deployment In a Traditional Iot-based Monitoring Systemmentioning

confidence: 99%

Novel node deployment scheme and reliability quantitative analysis for anIoT-based monitoring system

Tong¹,

Tian²,

Li³

2019

Turk J Elec Eng & Comp Sci

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The Internet of things (IoT) is highly suitable for military, environmental, agricultural, and other remote real-time monitoring applications. A reliable topology ensures a stable and dependable monitoring system. Considering the research of an IoT-based air pollution monitoring system for industrial emissions as background, this study proposes a novel dual redundant node deployment scheme. Specifically, hexagonal clustering is proposed for the internal regions.In addition, relationship and quantification formulas for a monitoring area are presented, and the communication range, total number of layers of the topology, and number of cluster headers are determined. Interruptions in a monitoring system may reduce the quality of IoT services. Therefore, sensor nodes are also deployed around the monitoring area (in outer regions). The basic external area is modeled and proposed as a rectangular, 1-covered isosceles triangle deployment plan with the objective of minimizing the number of sensor nodes. A quantitative formula is given using the sensing radius, width of the rectangle, and adjacent distance between nodes. Reliability is a critical index in IoT-based applications. Thus, the reliability of a hexagonal clustering topology is presented using reliability block diagrams. For a reliable remote transmission model, different redundant systems are implemented. Furthermore, the reliability value and mean time to failures are calculated. The results are later compared and analyzed quantitatively. This study presents important theoretical and application-based knowledge that can guarantee reliable service for an IoT-based monitoring system.

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Section: Node Deployment In a Traditional Iot-based Monitoring Systemmentioning

confidence: 99%

Novel node deployment scheme and reliability quantitative analysis for anIoT-based monitoring system

Tong¹,

Tian²,

Li³

2019

Turk J Elec Eng & Comp Sci

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“…An optimization formulation aimed at maximizing the reliability of the fault monitoring system is proposed [15,39,40,42,44]. Benatia et al [58] proposed a integrated multi-objectives deployment strategy by employing genetic algorithms under coverage, cost, connectivity constraints, to get near optimal solution for WSN deployment. We also developed a multi-objective optimization, which minimizes the fault unobservability, maximizes the system stability, and minimizes the cost for the whole system, under the constraints on detectability, stationarity, and limited resources [17,45].…”

Section:  mentioning

confidence: 99%

“…By employing the principles of GAs, many optimal sensor placement are developed in a complex system to optimize several competing evaluation criteria [26,33,58,[74][75][76][77][78][79]. Ren et al [31] developed a data-mining guided GA to solve the sensor distribution problem to achieve a maximal variance detection capability in a multi-station assembly process.…”

Section: Optimization Algorithmmentioning

confidence: 99%

A Comprehensive Survey of Sensor Deployment Strategies to Diagnose Discrete-Part Manufacturing System

He¹,

Jia²,

Zhao³

et al. 2018

Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering &Amp; Science (MEEES 2018)

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This paper presents a broad overview of the various sensor placement strategies to diagnose discrete-part manufacturing system. Due to the technical complexity, the performance of sensor system would be cursed by any modules of sensor placement strategies. Therefore, the current state of the sensor placement strategies is outlined with three key modules, namely cause-effect relationship model, optimization basis, and optimization algorithm, are surveyed in detail. The challenges faced by industry and academia are discussed and several principle conclusions are drawn, which could create a clear platform for the neophyte researchers for sensor deployment to diagnose discrete-part manufacturing system.

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“…In order to provide effective monitoring services in engineering applications, the nodes own position information must be provided [1,1]. The node position information is the key to whether the information obtained is valuable or not in WSN, especially for the target reconnaissance and tracking in the field of military and anti-terrorism [3,4]. It can be said that perceived data are meaningless if no node position information are provided.…”

Section: Introductionmentioning

confidence: 99%

“…(2) What kind of positioning algorithm should be used to obtain more accurate positioning accuracy? (3) What are the basic requirements to consider in terms of hardware resources and computational complexity when building a positioning algorithm?…”

Section: Introductionmentioning

confidence: 99%

Iterative Positioning Algorithm of the Target Node Based on Distance Correction in WSN

Chen¹,

Wang²,

Ouyang³

et al. 2019

Preprint

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The node position information is critical in the wireless sensor network (WSN). However, the existing positioning algorithms commonly have low positioning accuracy because of noise interferences in communication. To solve this problem, this paper presents an iterative positioning model based on distance correction to improve the positioning accuracy of the target node in WSN. First, the log-distance distribution model of received signal strength indication (RSSI) ranging is built and the noise impact factor is derived based on the model. Second, the initial position coordinates of the target node are obtained based on the triangle centroid localization algorithm, thereby calculating the distance deviation coefficient under the influence of noise. Then, the ratio of the distance measured by the log-normal distribution model to the median distance deviation coefficient is taken as the new distance between the anchor node and the target node. Based on the new distance, the triangular centroid positioning algorithm is used again to calculate the target node coordinates. Finally, the iterative positioning model is constructed, and the distance deviation coefficient is updated repeatedly to update the positioning result until the set number of iterations is reached. Experiment results show that the proposed iterative positioning model can improve positioning accuracy effectively.

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Multi-Objective WSN Deployment Using Genetic Algorithms Under Cost, Coverage, and Connectivity Constraints

Cited by 68 publications

References 35 publications

Novel node deployment scheme and reliability quantitative analysis for anIoT-based monitoring system

Novel node deployment scheme and reliability quantitative analysis for anIoT-based monitoring system

A Comprehensive Survey of Sensor Deployment Strategies to Diagnose Discrete-Part Manufacturing System

Iterative Positioning Algorithm of the Target Node Based on Distance Correction in WSN

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