120 research outputs found
Role of connectivity in congestion and decongestion in networks
We study network traffic dynamics in a two dimensional communication network
with regular nodes and hubs. If the network experiences heavy message traffic,
congestion occurs due to finite capacity of the nodes. We discuss strategies to
manipulate hub capacity and hub connections to relieve congestion and define a
coefficient of betweenness centrality (CBC), a direct measure of network
traffic, which is useful for identifying hubs which are most likely to cause
congestion. The addition of assortative connections to hubs of high CBC
relieves congestion very efficiently.Comment: 9 pages, 5 figures, the Proceedings of the 3rd International
Conference NEXT-SigmaPh
Sonification of Network Traffic Flow for Monitoring and Situational Awareness
Maintaining situational awareness of what is happening within a network is
challenging, not least because the behaviour happens within computers and
communications networks, but also because data traffic speeds and volumes are
beyond human ability to process. Visualisation is widely used to present
information about the dynamics of network traffic dynamics. Although it
provides operators with an overall view and specific information about
particular traffic or attacks on the network, it often fails to represent the
events in an understandable way. Visualisations require visual attention and so
are not well suited to continuous monitoring scenarios in which network
administrators must carry out other tasks. Situational awareness is critical
and essential for decision-making in the domain of computer network monitoring
where it is vital to be able to identify and recognize network environment
behaviours.Here we present SoNSTAR (Sonification of Networks for SiTuational
AwaReness), a real-time sonification system to be used in the monitoring of
computer networks to support the situational awareness of network
administrators. SoNSTAR provides an auditory representation of all the TCP/IP
protocol traffic within a network based on the different traffic flows between
between network hosts. SoNSTAR raises situational awareness levels for computer
network defence by allowing operators to achieve better understanding and
performance while imposing less workload compared to visual techniques. SoNSTAR
identifies the features of network traffic flows by inspecting the status flags
of TCP/IP packet headers and mapping traffic events to recorded sounds to
generate a soundscape representing the real-time status of the network traffic
environment. Listening to the soundscape allows the administrator to recognise
anomalous behaviour quickly and without having to continuously watch a computer
screen.Comment: 17 pages, 7 figures plus supplemental material in Github repositor
Enhance synchronizability by structural perturbations
In this paper, we investigate the collective synchronization of system of
coupled oscillators on Barab\'{a}si-Albert scale-free network. We propose an
approach of structural perturbations aiming at those nodes with maximal
betweenness. This method can markedly enhance the network synchronizability,
and is easy to be realized. The simulation results show that the eigenratio
will sharply decrease to its half when only 0.6% of those hub nodes are under
3-division processes when network size N=2000. In addition, the present study
also provides a theoretical evidence that the maximal betweenness plays a main
role in network synchronization.Comment: 4 pages, 3 eps figure
Stability and bifurcation in network traffic flow: A Poincar\'e map approach
Previous studies have shown that, in a diverge-merge network with two
intermediate links (the DM network), the kinematic wave model always admits
stationary solutions under constant boundary conditions, but periodic
oscillations can develop from empty initial conditions. Such contradictory
observations suggest that the stationary states be unstable. In this study we
develop a new approach to investigate the stability property of traffic flow in
this and other networks. Based on the observation that kinematic waves
propagate in a circular path when only one of the two intermediate links is
congested, we derive a one-dimensional, discrete Poincar\'e map in the out-flux
at a Poincar\'e section. We then prove that the fixed points of the Poincar\'e
map correspond to stationary flow-rates on the two links. With Lyapunov's first
method, we demonstrate that the Poincar\'e map can be finite-time stable,
asymptotically stable, or unstable. When unstable, the map is found to have
periodical points of period two, but no chaotic solutions. Comparing the
results with those in existing studies, we conclude that the Poincar\'e map can
be used to represent network-wide dynamics in the kinematic wave model. We
further analyze the bifurcation in the stability of the Poincar\'e map caused
by varying route choice proportions. We further apply the Poincar\'e map
approach to analyzing traffic patterns in more general and beltway
networks, which are sufficient and necessary structures for network-induced
unstable traffic and gridlock, respectively. This study demonstrates that the
Poincar\'e map approach can be efficiently applied to analyze traffic dynamics
in any road networks with circular information propagation and provides new
insights into unstable traffic dynamics caused by interactions among network
bottlenecks.Comment: 31 pages, 10 figures, 2 table
The Glasgow raspberry pi cloud: a scale model for cloud computing infrastructures
Data Centers (DC) used to support Cloud services
often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments
with a handful of machines. The recent introduction of the
Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable.
In this paper, we present the Glasgow Raspberry Pi Cloud
(PiCloud), a scale model of a DC composed of clusters of
Raspberry Pi devices. The PiCloud emulates every layer of a
Cloud stack, ranging from resource virtualisation to network
behaviour, providing a full-featured Cloud Computing research and educational environment
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
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