2,400 research outputs found
An Empirical Model of Packet Processing Delay of the Open vSwitch
Network virtualization offers flexibility by decoupling virtual network from
the underlying physical network. Software-Defined Network (SDN) could utilize
the virtual network. For example, in Software-Defined Networks, the entire
network can be run on commodity hardware and operating systems that use virtual
elements. However, this could present new challenges of data plane performance.
In this paper, we present an empirical model of the packet processing delay of
a widely used OpenFlow virtual switch, the Open vSwitch. In the empirical
model, we analyze the effect of varying Random Access Memory (RAM) and network
parameters on the performance of the Open vSwitch. Our empirical model captures
the non-network processing delays, which could be used in enhancing the network
modeling and simulation
Offloading in P4 Switch Integrated with Multiple Virtual Network Function Servers
Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two transformative technologies that offer distinct benefits. SDN virtualizes the control plane by separating it from the data plane, while NFV virtualizes the data plane by moving network functions from hardware and implementing them in software. Therefore, combining SDN and NFV can fully exploit the benefits of both technologies. As Programming Protocol-independent Packet Processors (P4) become popular due to its flexibility, traditional SDN switches are being replaced by P4 switches. In the P4+NFV architecture, network functions can be provided in both P4 switches (PNF) and NFV servers (VNF). However, to minimize packet delay, the offloading problem between P4 switches and NFV needs to be addressed. The novelty of our paper lies in investigating the offloading problem and evaluating the impact of employing multiple VNFs with varying computing capacities within the P4+NFV architecture. We also use M/M/1 queuing theory to derive the average packet delay and propose an optimization solution based on gradient descent to find out the optimal offloading probabilities of various VNF servers. Results show that optimal offloading from P4 switch to multiple VNFs can reduce the average packet delay from 4.76% to 40.02%
A hybrid queueing model for fast broadband networking simulation
PhDThis research focuses on the investigation of a fast simulation method for broadband
telecommunication networks, such as ATM networks and IP networks. As a result of
this research, a hybrid simulation model is proposed, which combines the analytical
modelling and event-driven simulation modelling to speeding up the overall
simulation.
The division between foreground and background traffic and the way of dealing with
these different types of traffic to achieve improvement in simulation time is the major
contribution reported in this thesis. Background traffic is present to ensure that proper
buffering behaviour is included during the course of the simulation experiments, but
only the foreground traffic of interest is simulated, unlike traditional simulation
techniques. Foreground and background traffic are dealt with in a different way.
To avoid the need for extra events on the event list, and the processing overhead,
associated with the background traffic, the novel technique investigated in this
research is to remove the background traffic completely, adjusting the service time of
the queues for the background traffic to compensate (in most cases, the service time
for the foreground traffic will increase). By removing the background traffic from the
event-driven simulator the number of cell processing events dealt with is reduced
drastically.
Validation of this approach shows that, overall, the method works well, but the
simulation using this method does have some differences compared with experimental
results on a testbed. The reason for this is mainly because of the assumptions behind
the analytical model that make the modelling tractable.
Hence, the analytical model needs to be adjusted. This is done by having a neural
network trained to learn the relationship between the input traffic parameters and the
output difference between the proposed model and the testbed. Following this
training, simulations can be run using the output of the neural network to adjust the
analytical model for those particular traffic conditions.
The approach is applied to cell scale and burst scale queueing to simulate an ATM
switch, and it is also used to simulate an IP router. In all the applications, the method
ensures a fast simulation as well as an accurate result
Assessing and augmenting SCADA cyber security: a survey of techniques
SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability
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