A parsimonious model of mobile partitioned networks with clustering

Piórkowski, Michał; Sarafijanovic-Djukic, Natasa; Grossglauser, Matthias

doi:10.1109/comsnets.2009.4808865

Cited by 236 publications

(162 citation statements)

References 31 publications

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“…We also used a real-life data set of cab mobility traces that were collected in the city of San Francisco [38]. This data set consists of 536 files, each of them containing the GPS coordinates of a cab during a period of time.…”

Section: Resultsmentioning

confidence: 99%

Microaggregation- and permutation-based anonymization of movement data

Domingo-Ferrer

Trujillo-Rasúa

2012

Information Sciences

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Movement data, that is, trajectories of mobile objects, are automatically collected in huge quantities by technologies such as GPS, GSM or RFID, among others. Publishing and exploiting such data is essential to improve transportation, to understand the dynamics of the economy in a region, etc. However, there are obvious threats to the privacy of individuals if their trajectories are published in a way which allows re-identification of the individual behind a trajectory. We contribute to the literature on privacy-preserving publication of trajectories by presenting a distance measure for trajectories which naturally considers both spatial and temporal aspects of trajectories, is computable in polynomial time, and can cluster trajectories not defined over the same time span. Our distance measure can be naturally instantiated using other existing similarity measures for trajectories that are appropriate for anonymization purposes. Then, we propose two heuristics for trajectory anonymization which yield anonymized trajectories formed by fully accurate true original locations. The first heuristic is based on trajectory microaggregation using the above distance and on location permutation; it effectively achieves trajectory k-anonymity. The second heuristic is based only on location permutation; it gives up trajectory k-anonymity and aims at location k-diversity. The strong point of the second heuristic is that it takes into account reachability constraints when computing anonymized trajectories. Experimental results on a synthetic data set and a real-life data set are presented; for similar privacy protection levels and most reasonable parameter choices, our two methods offer better utility than comparable previous proposals in the literature.

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Section: Resultsmentioning

confidence: 99%

Microaggregation- and permutation-based anonymization of movement data

Domingo-Ferrer

Trujillo-Rasúa

2012

Information Sciences

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“…The MIT dataset has been widely used to evaluate DTN protocols [49]; while being representative of some DTN settings (e.g., a university campus), its sparsity is not representative of DTN urban settings, where nodes are much more frequently connected (as in a MANET), but with short contact time (as in a DTN) [50]. To cover this scenario, we have thus expanded our evaluation to include an urban vehicular dataset [27].…”

Section: Simulation Settingsmentioning

confidence: 99%

“…To investigate the magnitude of the problem, we have conducted the following analysis: we have taken real mobility traces of two typical DTN settings: 100 MIT staff and students, moving around the university campus, for a period of nine months [26], and 100 taxicabs, moving within the San Francisco bay area, for a period of one month [27]. In both cases, nodes were posting messages to a varying number of recipients and at a varying publication rate (both parameters, i.e., number of message recipients and rate of publication, were set based on real data, as further discussed in Section 4).…”

Section: Motivationmentioning

confidence: 99%

“…• Mobility Traces: we experimented with two mobility datasets of different topological properties: the Reality Mining traces, containing mobility information of staff and students at the MIT campus [26], and a vehicular dataset of taxicabs in San Francisco [27]. The former contains colocation information from 96 subjects at the MIT campus over the course of the 2004-2005 academic year, to whom Bluetooth-enabled Nokia 6600 phones were given; colocation information was collected via frequent (5 minute) Bluetooth device discoveries.…”

Section: Simulation Settingsmentioning

confidence: 99%

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Fair content dissemination in participatory DTNs

Mashhadi¹,

Mokhtar²,

Capra³

2012

Ad Hoc Networks

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Thanks to advances in the computing capabilities and added functionalities of modern mobile devices, creating and consuming digital media on the move has never been so easy and popular. Most of the DTN routing protocols proposed in the literature to enable content sharing have been exploiting users' mobility patterns, in order to maximise the delivery probability, while minimising the overall network overhead (e.g., number of message replicas in the system, messages' path length). Common to all these protocols has been the assumption that devices are willing to participate in the content distribution network; however, because of battery constraints, participation cannot be taken for granted, especially if the very same subset of devices are continuously selected as content carriers, simply because of their mobility properties. Indeed, we demonstrate that state-of-the-art DTN routing protocols distribute load in a highly unfair manner, with detrimental effects on delivery once the assumption of unconditional participation is lifted. To overcome this limitation, we propose a load-balancing mechanism whereby nodes maintain local estimates of network workload, and use them to direct traffic towards the least loaded portion of the network. We implement the mechanism on top of a source-based DTN routing protocol, and demonstrate, by means of simulation using a variety of real mobility traces, that high delivery is now achieved without compromising fairness.

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“…In this paper we take advantage of two very interesting data sets: the Reality experiment, performed at MIT [5,6], and the Cabspotting data set [7,8].…”

Section: Data Setsmentioning

confidence: 99%

Self-management of Routing on Human Proximity Networks

Williamson

Cellai

Dobson

et al. 2009

Self-Organizing Systems

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Abstract. Many modern network applications, including sensor networks and MANETs, have dynamic topologies that reflect processes occurring in the outside world. These dynamic processes are a challenge to traditional information dissemination techniques, as the appropriate strategy changes according to the changes in topology. We show how network dynamics can be exploited to design a self-organising data dissemination mechanism using only node-level (local) information, which detects and adapts to periodic patterns in the network topology. We demonstrate our approach against real-world human-proximity networks.

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A parsimonious model of mobile partitioned networks with clustering

Cited by 236 publications

References 31 publications

Microaggregation- and permutation-based anonymization of movement data

Microaggregation- and permutation-based anonymization of movement data

Fair content dissemination in participatory DTNs

Self-management of Routing on Human Proximity Networks

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