30,651 research outputs found
Behaviors of susceptible-infected epidemics on scale-free networks with identical infectivity
In this article, we proposed a susceptible-infected model with identical
infectivity, in which, at every time step, each node can only contact a
constant number of neighbors. We implemented this model on scale-free networks,
and found that the infected population grows in an exponential form with the
time scale proportional to the spreading rate. Further more, by numerical
simulation, we demonstrated that the targeted immunization of the present model
is much less efficient than that of the standard susceptible-infected model.
Finally, we investigated a fast spreading strategy when only local information
is available. Different from the extensively studied path finding strategy, the
strategy preferring small-degree nodes is more efficient than that preferring
large-degree nodes. Our results indicate the existence of an essential
relationship between network traffic and network epidemic on scale-free
networks.Comment: 5 figures and 7 page
Local Search in Unstructured Networks
We review a number of message-passing algorithms that can be used to search
through power-law networks. Most of these algorithms are meant to be
improvements for peer-to-peer file sharing systems, and some may also shed some
light on how unstructured social networks with certain topologies might
function relatively efficiently with local information. Like the networks that
they are designed for, these algorithms are completely decentralized, and they
exploit the power-law link distribution in the node degree. We demonstrate that
some of these search algorithms can work well on real Gnutella networks, scale
sub-linearly with the number of nodes, and may help reduce the network search
traffic that tends to cripple such networks.Comment: v2 includes minor revisions: corrections to Fig. 8's caption and
references. 23 pages, 10 figures, a review of local search strategies in
unstructured networks, a contribution to `Handbook of Graphs and Networks:
From the Genome to the Internet', eds. S. Bornholdt and H.G. Schuster
(Wiley-VCH, Berlin, 2002), to be publishe
Low-Complexity Energy-Efficient Broadcasting in One-Dimensional Wireless Networks
In this paper, we investigate the transmission range assignment for N
wireless nodes located on a line (a linear wireless network) for broadcasting
data from one specific node to all the nodes in the network with minimum
energy. Our goal is to find a solution that has low complexity and yet performs
close to optimal. We propose an algorithm for finding the optimal assignment
(which results in the minimum energy consumption) with complexity O(N^2). An
approximation algorithm with complexity O(N) is also proposed. It is shown
that, for networks with uniformly distributed nodes, the linear-time
approximate solution obtained by this algorithm on average performs practically
identical to the optimal assignment. Both the optimal and the suboptimal
algorithms require the full knowledge of the network topology and are thus
centralized. We also propose a distributed algorithm of negligible complexity,
i.e., with complexity O(1), which only requires the knowledge of the adjacent
neighbors at each wireless node. Our simulations demonstrate that the
distributed solution on average performs almost as good as the optimal one for
networks with uniformly distributed nodes.Comment: 17 page
Performance evaluation of an efficient counter-based scheme for mobile ad hoc networks based on realistic mobility model
Flooding is the simplest and commonly used mechanism for broadcasting in mobile ad hoc networks (MANETs). Despite its simplicity, it can result in high redundant retransmission, contention and collision in the network, a phenomenon referred to as broadcast storm problem. Several probabilistic broadcast schemes have been proposed to mitigate this problem inherent with flooding. Recently, we have proposed a hybrid-based scheme as one of the probabilistic scheme, which combines the advantages of pure probabilistic and counter-based schemes to yield a significant performance improvement. Despite these considerable numbers of proposed broadcast schemes, majority of these schemes’ performance evaluation was based on random waypoint model. In this paper, we evaluate the performance of our broadcast scheme using a community based mobility model which is based on social network theory and compare it against widely used random waypoint mobility model. Simulation results have shown that using unrealistic movement pattern does not truly reflect on the actual performance of the scheme in terms of saved-rebroadcast, reachability and end to end delay
Time walkers and spatial dynamics of ageing information
The distribution of information is essential for living system's ability to
coordinate and adapt. Random walkers are often used to model this distribution
process and, in doing so, one effectively assumes that information maintains
its relevance over time. But the value of information in social and biological
systems often decay and must continuously be updated. To capture the spatial
dynamics of ageing information, we introduce time walkers. A time walker moves
like a random walker, but interacts with traces left by other walkers, some
representing older information, some newer. The traces forms a navigable
information landscape. We quantify the dynamical properties of time walkers
moving on a two-dimensional lattice and the quality of the information
landscape generated by their movements. We visualise the self-similar landscape
as a river network, and show that searching in this landscape is superior to
random searching and scales as the length of loop-erased random walks
Search in Power-Law Networks
Many communication and social networks have power-law link distributions,
containing a few nodes which have a very high degree and many with low degree.
The high connectivity nodes play the important role of hubs in communication
and networking, a fact which can be exploited when designing efficient search
algorithms. We introduce a number of local search strategies which utilize high
degree nodes in power-law graphs and which have costs which scale sub-linearly
with the size of the graph. We also demonstrate the utility of these strategies
on the Gnutella peer-to-peer network.Comment: 17 pages, 14 figure
Networking - A Statistical Physics Perspective
Efficient networking has a substantial economic and societal impact in a
broad range of areas including transportation systems, wired and wireless
communications and a range of Internet applications. As transportation and
communication networks become increasingly more complex, the ever increasing
demand for congestion control, higher traffic capacity, quality of service,
robustness and reduced energy consumption require new tools and methods to meet
these conflicting requirements. The new methodology should serve for gaining
better understanding of the properties of networking systems at the macroscopic
level, as well as for the development of new principled optimization and
management algorithms at the microscopic level. Methods of statistical physics
seem best placed to provide new approaches as they have been developed
specifically to deal with non-linear large scale systems. This paper aims at
presenting an overview of tools and methods that have been developed within the
statistical physics community and that can be readily applied to address the
emerging problems in networking. These include diffusion processes, methods
from disordered systems and polymer physics, probabilistic inference, which
have direct relevance to network routing, file and frequency distribution, the
exploration of network structures and vulnerability, and various other
practical networking applications.Comment: (Review article) 71 pages, 14 figure
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