Are you moved by your social network application?

Mtibaa, Abderrahmen; Chaintreau, Augustin; LeBrun, Jason; Oliver, Earl; Pietilainen, Anna-Kaisa; Diot, Christophe

doi:10.1145/1397735.1397751

Cited by 61 publications

(39 citation statements)

References 10 publications

(13 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Spatio-temporal aspects have also been studied for the analysis of delay and data delivery in DTN networks [7,3]. The Kempe-Kleinberg model has also been adapted for social networks analysis [5,13,1], however the focus of these works is on the local characteristics of time-varying networks; global aspects of the information processes in these networks are not captured.…”

Section: Introductionmentioning

confidence: 99%

Characterising temporal distance and reachability in mobile and online social networks

Tang

Musolesi

Mascolo

et al. 2010

SIGCOMM Comput. Commun. Rev.

129

View full text Add to dashboard Cite

The analysis of social and technological networks has attracted a lot of attention as social networking applications and mobile sensing devices have given us a wealth of real data. Classic studies looked at analysing static or aggregated networks, i.e., networks that do not change over time or built as the results of aggregation of information over a certain period of time. Given the soaring collections of measurements related to very large, real network traces, researchers are quickly starting to realise that connections are inherently varying over time and exhibit more dimensionality than static analysis can capture.In this paper we propose new temporal distance metrics to quantify and compare the speed (delay) of information diffusion processes taking into account the evolution of a network from a global view. We show how these metrics are able to capture the temporal characteristics of time-varying graphs, such as delay, duration and time order of contacts (interactions), compared to the metrics used in the past on static graphs. We also characterise network reachability with the concepts of in-and out-components. Then, we generalise them with a global perspective by defining temporal connected components. As a proof of concept we apply these techniques to two classes of time-varying networks, namely connectivity of mobile devices and interactions on an online social network.

show abstract

Section: Introductionmentioning

confidence: 99%

Characterising temporal distance and reachability in mobile and online social networks

Tang

Musolesi

Mascolo

et al. 2010

SIGCOMM Comput. Commun. Rev.

129

View full text Add to dashboard Cite

show abstract

“…However, as real and large-scale traces of human mobility started to be collected, scientists demonstrated that human movement is not random at all (e.g., [18,19,20,21]); rather, it can be predicted to a large extent (e.g., [22,23]). A new generation of DTN protocols has then been proposed, that reasons upon human mobility patterns, in a quest to better trade delivery with overhead (e.g., [1,24,25,7]). Whilst largely successful in attaining this goal, all DTN routing protocols heavily rely on the voluntary participation of nodes in the network to forward content.…”

Section: Motivationmentioning

confidence: 99%

Fair content dissemination in participatory DTNs

Mashhadi¹,

Mokhtar²,

Capra³

2012

Ad Hoc Networks

View full text Add to dashboard Cite

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.

show abstract

“…Routing algorithms can benefit by incorporating this additional information. It has been shown that forwarding messages through social neighbours can achieve better delivery performance in a small conference environment than random forwarding [34].…”

Section: Peoplerank Routingmentioning

confidence: 99%

Routing in Opportunistic Networks

Santi

2012

Mobility Models for Next Generation Wireless Networks

View full text Add to dashboard Cite

Are you moved by your social network application?

Cited by 61 publications

References 10 publications

Characterising temporal distance and reachability in mobile and online social networks

Characterising temporal distance and reachability in mobile and online social networks

Fair content dissemination in participatory DTNs

Routing in Opportunistic Networks

Contact Info

Product

Resources

About