More is More: The Benefits of Denser Sensor Deployment

Johnson, Matthew; Sarıöz, Deniz; Bar-Noy, Amotz; Brown, Ted; Verma, Dinesh; Wu, Chai Wah

doi:10.1109/infcom.2009.5061942

Cited by 18 publications

(13 citation statements)

References 16 publications

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“…Connectivity and barrier coverage have been extensively studied in research community (e.g., see [2], [4], [5], [8], [17], [24], [34] and [43]). The work by [34] introduced two notions of probabilistic barrier coverage: weak and strong barrier coverage.…”

Section: A Related Workmentioning

confidence: 99%

On the Energy in Displacement of Random Sensors for Connectivity and Interference

Kapelko

2020

Proceedings of the 21st International Conference on Distributed Computing and Networking

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This paper investigates the problem of the minimilization of energy consumption in reallocation of wireless mobile sensors network (WMSN) to assure good communication without interference.Fix d ∈ N \ {0}. Assume n sensors are initially randomly placed in the hyperoctant [0, ∞) d according to d identical and independent Poisson processes each with arrival rate λ > 0.Let 0 < s ≤ v be given real numbers. We are allowed to move the sensors, so that every two consecutive sensors are placed at distance greater than or equal to s and less than or equal to v.Fix a ≥ 1. Assume that i−th sensor is displaced a distance equal to m(i). The cost measure for the displacement of the team of sensors is the sum n i=1 d a i (a−total movement). In this work, we discover and explain a sharp decline and a sharp increase (a threshold phenomena) in the expected minimal a−total movement around the interference-connectivity distances s, v equal to 1 λ .

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Section: A Related Workmentioning

confidence: 99%

On the Energy in Displacement of Random Sensors for Connectivity and Interference

Kapelko

2020

Proceedings of the 21st International Conference on Distributed Computing and Networking

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“…Other authors have focused on minimizing the number of network nodes required to observe a region by reducing the overlapping regions among their coverage zones. In this context, a result worth mentioning is that the hexagon grid lattice is a single-coverage optimal grid [15]. However, small displacement of one network node may create holes, resulting in blind regions within the wireless network.…”

Section: Related Workmentioning

confidence: 99%

LEA: An Algorithm to Estimate the Level of Location Exposure in Infrastructure-Based Wireless Networks

García¹,

Gómez²,

Lopez‐Guerrero³

et al. 2017

Mobile Information Systems

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Location privacy in wireless networks is nowadays a major concern. This is due to the fact that the mere fact of transmitting may allow a network to pinpoint a mobile node. We consider that a first step to protect a mobile node in this situation is to provide it with the means to quantify how accurately a network establishes its position. To achieve this end, we introduce the location-exposure algorithm (LEA), which runs on the mobile terminal only and whose operation consists of two steps. In the first step, LEA discovers the positions of nearby network nodes and uses this information to emulate how they estimate the position of the mobile node. In the second step, it quantifies the level of exposure by computing the distance between the position estimated in the first step and its true position. We refer to these steps as alocation-exposureproblem. We tested our proposal with simulations and testbed experiments. These results show the ability of LEA to reproduce the location of the mobile node, as seen by the network, and to quantify the level of exposure. This knowledge can help the mobile user decide which actions should be performed before transmitting.

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“…at a distance σ ≤ 2R s . A similar approach has been proposed in [16] for full coverage. The value of sigma can be tuned according to the precision of the positioning system.…”

Section: Network Model and Problem Formulationmentioning

confidence: 99%

MobiBar: Barrier Coverage with Mobile Sensors

Silvestri

2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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Critical homeland security applications such as monitoring zones contaminated by chemical or biological attacks and monitoring the spread of forest fires, require the timely creation of barrier of sensors along the border to be monitored. The strict time requirements and the hazardous nature of these contexts impede manual sensor positioning. Mobile Wireless Sensor Networks have the potential to meet the desired coverage requirements, by exploiting the device locomotion capabilities. In this paper we propose MOBIBAR, a distributed and asynchronous algorithm for k-barrier coverage with mobile sensors. We formally prove that MOBIBAR terminates in a finite time and that the final deployment provides the maximum level of barrier coverage with the available sensors. We compare MOBIBAR to a recent virtual force-based approach by means of simulations, which show the superiority of our solution. Furthermore, we show the self-healing capability of MOBIBAR to quickly recover from sudden sensor faults

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More is More: The Benefits of Denser Sensor Deployment

Cited by 18 publications

References 16 publications

On the Energy in Displacement of Random Sensors for Connectivity and Interference

On the Energy in Displacement of Random Sensors for Connectivity and Interference

LEA: An Algorithm to Estimate the Level of Location Exposure in Infrastructure-Based Wireless Networks

MobiBar: Barrier Coverage with Mobile Sensors

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