Opportunistic Sampling for Joint Population Size and Density Estimation

Naini, Farid Movahedi; Dousse, Olivier; Thiran, Patrick; Vetterli, Martin

doi:10.1109/tmc.2015.2393302

Cited by 4 publications

(4 citation statements)

References 39 publications

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“…Human mobility models [5], [6], [26] indicates that a hybrid approach could benefit from the resiliency and robustness of controlled flooding in general, while leveraging overlays where and when they are beneficial, that is, around the points of interests (POI) identified at large gatherings [8], [9].…”

Section: Towards Emergent Overlaysmentioning

confidence: 99%

“…Use case and experiment model. We consider a set of 600 mobile nodes, the placement and mobility of which are inspired by real-life measurements of crowds at large events [8], [9]. Figure 6 portrays the starting node positions in the simulated setup.…”

Section: A Experimental Setupmentioning

confidence: 99%

“…Second, there are points of attraction around which users tend to aggregate [7], leading to zones of heterogeneous density. Heterogeneity in space was confirmed by an experiment at the Paléo music festival in Switzerland [8]. The authors performed an estimation of the population size and of its spatial distribution by collecting unique MAC addresses from a significant portion of attendees' mobile phones that were discoverable via bluetooth.…”

Section: Introductionmentioning

confidence: 99%

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Emergent Overlays for Adaptive MANET Broadcast

Carvajal-Gómez

Elkhatib

Réveillère

et al. 2019

2019 38th Symposium on Reliable Distributed Systems (SRDS)

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Mobile Ad-Hoc Networks (MANETs) allow distributed applications where no fixed network infrastructure is available. MANETs use wireless communication subject to faults and uncertainty, and must support efficient broadcast. Controlled flooding is suitable for highly-dynamic networks, while overlay-based broadcast is suitable for dense and more static ones. Density and mobility vary significantly over a MANET deployment area. We present the design and implementation of emergent overlays for efficient and reliable broadcast in heterogeneous MANETs. This adaptation technique allows nodes to automatically switch from controlled flooding to the use of an overlay. Interoperability protocols support the integration of both protocols in a single heterogeneous system. Coordinated adaptation policies allow regions of nodes to autonomously and collectively emerge and dissolve overlays. Our simulation of the full network stack of 600 mobile nodes shows that emergent overlays reduce energy consumption, and improve reliability and coverage compared to single protocols and to two previouslyproposed adaptation techniques.

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Section: Towards Emergent Overlaysmentioning

confidence: 99%

Section: A Experimental Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Emergent Overlays for Adaptive MANET Broadcast

Carvajal-Gómez

Elkhatib

Réveillère

et al. 2019

2019 38th Symposium on Reliable Distributed Systems (SRDS)

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“…Crowdsourcing approaches have been investigated for different applications, for example, for estimating both density and number of attendees of large events [21]. Many works pertain to the use of crowdsourcing for NCL discovery.…”

Section: Related Workmentioning

confidence: 99%

Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance

Checco

Lancia

Leith

2018

Wireless Communications and Mobile Computing

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In modern wireless networks deployments, each serving node needs to keep its Neighbour Cell List (NCL) constantly up to date to keep track of network changes. The time needed by each serving node to update its NCL is an important parameter of the network's reliability and performance. An adequate estimate of such parameter enables a significant improvement of self-configuration functionalities. This paper focuses on the update time of NCLs when an approach of crowdsourced user reports is adopted. In this setting, each user periodically reports to the serving node information about the set of nodes sensed by the user itself. We show that, by mapping the local topological structure of the network onto states of increasing knowledge, a crisp mathematical framework can be obtained, which allows in turn for the use of a variety of user mobility models. Further, using a simplified mobility model we show how to obtain useful upper bounds on the expected time for a serving node to gain Full Knowledge of its local neighbourhood.

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