2,033 research outputs found
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
Social-Aware Forwarding Improves Routing Performance in Pocket Switched Networks
Several social-aware forwarding strategies have been recently introduced in
opportunistic networks, and proved effective in considerably in- creasing
routing performance through extensive simulation studies based on real-world
data. However, this performance improvement comes at the expense of storing a
considerable amount of state information (e.g, history of past encounters) at
the nodes. Hence, whether the benefits on routing performance comes directly
from the social-aware forwarding mechanism, or indirectly by the fact state
information is exploited is not clear. Thus, the question of whether
social-aware forwarding by itself is effective in improving opportunistic
network routing performance remained unaddressed so far. In this paper, we give
a first, positive answer to the above question, by investigating the expected
message delivery time as the size of the net- work grows larger
Mobile Social Networking aided content dissemination in heterogeneous networks
Since more and more mobile applications are based on the proliferation of social information, the study of Mobile Social Net-works (MSNs) combines social sciences and wireless communications. Operating wireless networks more efficiently by exploiting social relationships between MSN users is an appealing but challenging option for network operators. An MSN-aided content dissemination technique is presented as a potential ex-tension of conventional cellular wireless net-works in order to satisfy growing data traffic. By allowing the MSN users to create a self-organized ad hoc network for spontaneously disseminating contents, the network operator may be able to reduce the operational costs and simultaneously achieve an improved network performance. In this paper, we first summarize the basic features of the MSN architecture, followed by a survey of the factors which may affect MSN-aided content dissemination. Using a case study, we demonstrate that one can save resources of the Base Station (BS) while substantially lowering content dissemination delay. Finally, other potential applications of MSN-aided content dissemination are introduced, and a range of future challenges are summarized
Orion Routing Protocol for Delay-Tolerant Networks
In this paper, we address the problem of efficient routing in delay tolerant
network. We propose a new routing protocol dubbed as ORION. In ORION, only a
single copy of a data packet is kept in the network and transmitted, contact by
contact, towards the destination. The aim of the ORION routing protocol is
twofold: on one hand, it enhances the delivery ratio in networks where an
end-to-end path does not necessarily exist, and on the other hand, it minimizes
the routing delay and the network overhead to achieve better performance. In
ORION, nodes are aware of their neighborhood by the mean of actual and
statistical estimation of new contacts. ORION makes use of autoregressive
moving average (ARMA) stochastic processes for best contact prediction and
geographical coordinates for optimal greedy data packet forwarding. Simulation
results have demonstrated that ORION outperforms other existing DTN routing
protocols such as PRoPHET in terms of end-to-end delay, packet delivery ratio,
hop count and first packet arrival
Wireless Communications in the Era of Big Data
The rapidly growing wave of wireless data service is pushing against the
boundary of our communication network's processing power. The pervasive and
exponentially increasing data traffic present imminent challenges to all the
aspects of the wireless system design, such as spectrum efficiency, computing
capabilities and fronthaul/backhaul link capacity. In this article, we discuss
the challenges and opportunities in the design of scalable wireless systems to
embrace such a "bigdata" era. On one hand, we review the state-of-the-art
networking architectures and signal processing techniques adaptable for
managing the bigdata traffic in wireless networks. On the other hand, instead
of viewing mobile bigdata as a unwanted burden, we introduce methods to
capitalize from the vast data traffic, for building a bigdata-aware wireless
network with better wireless service quality and new mobile applications. We
highlight several promising future research directions for wireless
communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications
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