On the Cover Time of Random Geometric Graphs

Avin, Chen; Ercal, Gunes

doi:10.1007/11523468_55

Cited by 49 publications

(57 citation statements)

References 24 publications

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“…One can see that partial cover can be achieved in O(N ) number of steps/stops/locations, whereas complete coverage is more difficult to achieve and requires, O(NlogN) in the best case scenario or polynomial in N for other cases. These findings have been confirmed independently for random geometric gaphs in [18].…”

Section: B Results For the 0-hop Data Collection Schemessupporting

confidence: 59%

Sink mobility schemes for data extraction in large scale WSNs under single or zero hop data forwarding

Tzevelekas

Stavrakakis

2010

2010 European Wireless Conference (EW)

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Abstract-A mobile sink is widely considered to facilitate the data collection from energy constrained sensor fields, by having the sink come close to the sensors and conserving precious sensor node energy. The effectiveness of such a data collection approach can be measured in terms of the sensor energy conserved and the time required to collect the sensor data from the field (or, equivalently, the length of the trajectory implemented by the mobile sink).In this paper we explore two important dimensions in the design of mobile sink-based data collection schemes. One dimension refers to how close to the sensor nodes the sink moves to, to collect the data, which impacts on the transmission energy expenditure by the sensor node. The other dimension refers to the way the sink moves through the sensor field, to collect the data, which impacts on the delay in collecting the data. To capture the first dimension, the 0-hop and 1-hop data collection schemes are considered and studied; at the same time, two "extreme" approaches to the sink mobility process are considered: a (topology unaware) random walk-based sink mobility scheme and a (topology aware, optimal) deterministic sink mobility scheme. Through the analytic and simulative study presented in this paper, an understanding of the level of the trade-offs involved between the energy spent by the sensor nodes and the delay in completing the data collection process is obtained.

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Section: B Results For the 0-hop Data Collection Schemessupporting

confidence: 59%

Sink mobility schemes for data extraction in large scale WSNs under single or zero hop data forwarding

Tzevelekas

Stavrakakis

2010

2010 European Wireless Conference (EW)

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“…A similar work to this one is described by Mian et al [44], where the authors propose the so-called "attenuation" metric that shows the speed of the random walker's movement. Cover time is examined by Avin and Ercal [45]. There are interesting theoretical results regarding the achieved optimal cover time with high probability, providing tight lower bounds from the chosen radius of the geometric graphs.…”

Section: Related Workmentioning

confidence: 99%

Random Walker Coverage Analysis for Information Dissemination in Wireless Sensor Networks

2017

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Abstract:The increasing technological progress in electronics provides network nodes with new and enhanced capabilities that allow the revisit of the traditional information dissemination (and collection) problem. The probabilistic nature of information dissemination using random walkers is exploited here to deal with challenges imposed by unconventional modern environments. In such systems, node operation is not deterministic (e.g., does not depend only on network nodes' battery), but it rather depends on the particulars of the ambient environment (e.g., in the case of energy harvesting: sunshine, wind). The mechanism of information dissemination using one random walker is studied and analyzed in this paper under a different and novel perspective. In particular, it takes into account the stochastic nature of random walks, enabling further understanding of network coverage. A novel and original analysis is presented, which reveals the evolution network coverage by a random walker with respect to time. The derived analytical results reveal certain additional interesting aspects regarding network coverage, thus shedding more light on the random walker mechanism. Further analytical results, regarding the walker's spatial movement and its associated neighborhood, are also confirmed through experimentation. Finally, simulation results considering random geometric graph topologies, which are suitable for modeling mobile environments, support and confirm the analytical findings.

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“…In W_AntNet, the forward ants perform random walks to search for the destination. Therefore, the worst-case routing overhead for a single update of the routing tables [2] is ( log ). Moreover, the number of updates required for routing table convergence, i.e.…”

Section: Routing Overhead For W_antnetmentioning

confidence: 99%