1,777 research outputs found
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
On the Dynamics of Human Proximity for Data Diffusion in Ad-Hoc Networks
We report on a data-driven investigation aimed at understanding the dynamics
of message spreading in a real-world dynamical network of human proximity. We
use data collected by means of a proximity-sensing network of wearable sensors
that we deployed at three different social gatherings, simultaneously involving
several hundred individuals. We simulate a message spreading process over the
recorded proximity network, focusing on both the topological and the temporal
properties. We show that by using an appropriate technique to deal with the
temporal heterogeneity of proximity events, a universal statistical pattern
emerges for the delivery times of messages, robust across all the data sets.
Our results are useful to set constraints for generic processes of data
dissemination, as well as to validate established models of human mobility and
proximity that are frequently used to simulate realistic behaviors.Comment: A. Panisson et al., On the dynamics of human proximity for data
diffusion in ad-hoc networks, Ad Hoc Netw. (2011
Exploiting Temporal Complex Network Metrics in Mobile Malware Containment
Malicious mobile phone worms spread between devices via short-range Bluetooth
contacts, similar to the propagation of human and other biological viruses.
Recent work has employed models from epidemiology and complex networks to
analyse the spread of malware and the effect of patching specific nodes. These
approaches have adopted a static view of the mobile networks, i.e., by
aggregating all the edges that appear over time, which leads to an approximate
representation of the real interactions: instead, these networks are inherently
dynamic and the edge appearance and disappearance is highly influenced by the
ordering of the human contacts, something which is not captured at all by
existing complex network measures. In this paper we first study how the
blocking of malware propagation through immunisation of key nodes (even if
carefully chosen through static or temporal betweenness centrality metrics) is
ineffective: this is due to the richness of alternative paths in these
networks. Then we introduce a time-aware containment strategy that spreads a
patch message starting from nodes with high temporal closeness centrality and
show its effectiveness using three real-world datasets. Temporal closeness
allows the identification of nodes able to reach most nodes quickly: we show
that this scheme can reduce the cellular network resource consumption and
associated costs, achieving, at the same time, a complete containment of the
malware in a limited amount of time.Comment: 9 Pages, 13 Figures, In Proceedings of IEEE 12th International
Symposium on a World of Wireless, Mobile and Multimedia Networks (WOWMOM '11
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