2,412 research outputs found
Improving VANET Protocols via Network Science
Developing routing protocols for Vehicular Ad Hoc Networks (VANETs) is a
significant challenge in these large, self- organized and distributed networks.
We address this challenge by studying VANETs from a network science perspective
to develop solutions that act locally but influence the network performance
globally. More specifically, we look at snapshots from highway and urban VANETs
of different sizes and vehicle densities, and study parameters such as the node
degree distribution, the clustering coefficient and the average shortest path
length, in order to better understand the networks' structure and compare it to
structures commonly found in large real world networks such as small-world and
scale-free networks. We then show how to use this information to improve
existing VANET protocols. As an illustrative example, it is shown that, by
adding new mechanisms that make use of this information, the overhead of the
urban vehicular broadcasting (UV-CAST) protocol can be reduced substantially
with no significant performance degradation.Comment: Proceedings of the 2012 IEEE Vehicular Networking Conference (VNC),
Korea, November 201
On Leveraging Partial Paths in Partially-Connected Networks
Mobile wireless network research focuses on scenarios at the extremes of the
network connectivity continuum where the probability of all nodes being
connected is either close to unity, assuming connected paths between all nodes
(mobile ad hoc networks), or it is close to zero, assuming no multi-hop paths
exist at all (delay-tolerant networks). In this paper, we argue that a sizable
fraction of networks lies between these extremes and is characterized by the
existence of partial paths, i.e. multi-hop path segments that allow forwarding
data closer to the destination even when no end-to-end path is available. A
fundamental issue in such networks is dealing with disruptions of end-to-end
paths. Under a stochastic model, we compare the performance of the established
end-to-end retransmission (ignoring partial paths), against a forwarding
mechanism that leverages partial paths to forward data closer to the
destination even during disruption periods. Perhaps surprisingly, the
alternative mechanism is not necessarily superior. However, under a stochastic
monotonicity condition between current v.s. future path length, which we
demonstrate to hold in typical network models, we manage to prove superiority
of the alternative mechanism in stochastic dominance terms. We believe that
this study could serve as a foundation to design more efficient data transfer
protocols for partially-connected networks, which could potentially help
reducing the gap between applications that can be supported over disconnected
networks and those requiring full connectivity.Comment: Extended version of paper appearing at IEEE INFOCOM 2009, April
20-25, Rio de Janeiro, Brazi
PROTECT: Proximity-based Trust-advisor using Encounters for Mobile Societies
Many interactions between network users rely on trust, which is becoming
particularly important given the security breaches in the Internet today. These
problems are further exacerbated by the dynamics in wireless mobile networks.
In this paper we address the issue of trust advisory and establishment in
mobile networks, with application to ad hoc networks, including DTNs. We
utilize encounters in mobile societies in novel ways, noticing that mobility
provides opportunities to build proximity, location and similarity based trust.
Four new trust advisor filters are introduced - including encounter frequency,
duration, behavior vectors and behavior matrices - and evaluated over an
extensive set of real-world traces collected from a major university. Two sets
of statistical analyses are performed; the first examines the underlying
encounter relationships in mobile societies, and the second evaluates DTN
routing in mobile peer-to-peer networks using trust and selfishness models. We
find that for the analyzed trace, trust filters are stable in terms of growth
with time (3 filters have close to 90% overlap of users over a period of 9
weeks) and the results produced by different filters are noticeably different.
In our analysis for trust and selfishness model, our trust filters largely undo
the effect of selfishness on the unreachability in a network. Thus improving
the connectivity in a network with selfish nodes.
We hope that our initial promising results open the door for further research
on proximity-based trust
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