Evaluating the optimal sensor placement for smoke detection

Maksimović, Mirjana; Milosevic, V.

doi:10.2298/yjor140312002m

Cited by 16 publications

(6 citation statements)

References 9 publications

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“…Deterministic deployment approaches aim to calculate the optimal location of network nodes that achieves a desired objective. These methods can be classified into four different categories, as we have summarized below: 1) Grid-based methods: Examples include [24], [25] in which the locations of network nodes are determined based on a grid shape such as triangular, rectangular, or hexagonal grid pattern. These methods are favorable due to their simplicity; however, they consider a homogeneous setting and do not account for the heterogeneity of network nodes; thus, they perform poorly when the WSN is comprised of nodes with different characteristics.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

Karimi-Bidhendi

Guo

Jafarkhani

2022

IEEE Trans. Wireless Commun.

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We study a heterogeneous wireless sensor network (WSN) where N heterogeneous access points (APs) gather data from densely deployed sensors and transmit their sensed information to M heterogeneous fusion centers (FCs) via multi-hop wireless communication. The heterogeneous optimal deployment of APs and FCs is modeled as an optimization problem with total wireless communication power consumption of the network as its objective function. We consider both static WSNs, where APs and FCs retain their deployed position, and mobile WSNs where APs and FCs can move from their initial deployment to their optimal locations. Based on the derived necessary conditions for the optimal deployment in static WSNs, we propose an iterative algorithm to deploy APs and FCs. In addition, we study the necessary conditions of the optimal movement-efficient deployment in mobile WSNs with constrained movement energy and present iterative algorithms to find such deployments, accordingly.Simulation results show that our proposed deployment algorithms outperform the existing methods in the literature, and achieve a lower total wireless communication power in both static and mobile WSNs.

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Section: Related Workmentioning

confidence: 99%

Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

Karimi-Bidhendi

Guo

Jafarkhani

2022

IEEE Trans. Wireless Commun.

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“…They recommended the triangular lattice pattern as suitable deployment pattern in the case of required coverage level is ≥ 3 with ratio R C /r s ≥ √ 3. Finding the optimal deployment of sensors, in order to achieve full area coverage and long life for sensor nodes using a minimum number of nodes was discussed in [27]. They considered three deployment strategies: grid, triangular, and strip.…”

Section: ) Grid-based Techniquesmentioning

confidence: 99%

Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey

et al. 2019

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Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote locations. A large number of sensor nodes are deployed in the monitoring area. Therefore, deploying the minimum number of nodes that maintain full coverage and connectivity is of immense importance for research. Hence, coverage and connectivity issues, besides maximizing the network lifetime, represented the main concern to be considered in this paper. The key point of this paper is to classify different coverage techniques in WSNs into three main parts: coverage based on classical deployment techniques, coverage based on meta-heuristic techniques, and coverage based on self-scheduling techniques. Moreover, multiple comparisons among these techniques are provided considering their advantages and disadvantages. Additionally, performance metrics that must be considered in WSNs and comparison among different WSNs simulators are provided. Finally, open research issues, as well as recommendations for researchers, are discussed. INDEX TERMS Coverage, connectivity, deployment techniques, power consumption, wireless sensor network (WSN).

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“…In [21] discuss three placement strategies known as the grid, triangular and strip to in a WSN used for detecting smoke. The aim is to ensure maximum network lifetime and maximum coverage with a minimum number of sensor nodes.…”

Section: B Static Placementmentioning

confidence: 99%

A Review on Sensor Node Placement Techniques in Wireless Sensor Networks

Abidin¹,

Din²,

Radzi³

et al. 2017

International Journal on Advanced Science, Engineering and Information Technology

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One way to provide Wireless Sensor Network (WSN) with maximum coverage, maximum connectivity, minimum deployment cost and minimum energy consumption is through an effective planning mechanism in arranging an optimum number of sensor nodes. Proper planning will provide a cost-effective deployment by having optimal placements for the sensor nodes. Sensor node placement schemes are needed to accommodate the balance of coverage and energy consumption since closer sensor nodes not only reduces the energy consumption but will result in the network coverage becoming smaller. This paper critically reviews the research and development work done in sensor node placement. Based on the review, the design objectives that need to be considered are identified. Most of the work reviewed focused on two or three design objectives.

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Evaluating the optimal sensor placement for smoke detection

Cited by 16 publications

References 9 publications

Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey

A Review on Sensor Node Placement Techniques in Wireless Sensor Networks

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