100,014 research outputs found
Overview of three-phase inverter topologies for distributed generation purposes
The increasing presence of single-phase distributed generators and unbalanced loads in the electric power system may lead to unbalance of the three phase voltages, resulting in increased losses and heating. Distribution network operators are seeking to install larger DG units (viz. kVA in Belgium) by means of three-phase connections instead of single-phase to reduce voltage unbalance. There are several possible topologies to connect the DG units to the three-phase distribution network. These topologies can be divided into three groups: the three-phase three-wire inverters, the three-phase four-wire inverters and the multilevel inverters. In this paper, an overview of the aforementioned topologies is given
SDN-based virtual machine management for cloud data centers
Software-Defined Networking (SDN) is an emerging paradigm to logically centralize the network control plane and automate the configuration of individual network elements. At the same time, in Cloud Data Centers (DCs), even though network and server resources converge over the same infrastructure and typically over a single administrative entity, disjoint control mechanisms are used for their respective management. In this paper, we propose a unified server-network control mechanism for converged ICT environments. We present a SDN-based orchestration framework for live Virtual Machine (VM) management where server hypervisors exploit temporal network information to migrate VMs and minimize the network-wide communication cost of the resulting traffic dynamics. A prototype implementation is presented and Mininet is used to evaluate the impact of diverse orchestration algorithms
Self-Modeling Based Diagnosis of Software-Defined Networks
Networks built using SDN (Software-Defined Networks) and NFV (Network
Functions Virtualization) approaches are expected to face several challenges
such as scalability, robustness and resiliency. In this paper, we propose a
self-modeling based diagnosis to enable resilient networks in the context of
SDN and NFV. We focus on solving two major problems: On the one hand, we lack
today of a model or template that describes the managed elements in the context
of SDN and NFV. On the other hand, the highly dynamic networks enabled by the
softwarisation require the generation at runtime of a diagnosis model from
which the root causes can be identified. In this paper, we propose finer
granular templates that do not only model network nodes but also their
sub-components for a more detailed diagnosis suitable in the SDN and NFV
context. In addition, we specify and validate a self-modeling based diagnosis
using Bayesian Networks. This approach differs from the state of the art in the
discovery of network and service dependencies at run-time and the building of
the diagnosis model of any SDN infrastructure using our templates
Graph Annotations in Modeling Complex Network Topologies
The coarsest approximation of the structure of a complex network, such as the
Internet, is a simple undirected unweighted graph. This approximation, however,
loses too much detail. In reality, objects represented by vertices and edges in
such a graph possess some non-trivial internal structure that varies across and
differentiates among distinct types of links or nodes. In this work, we
abstract such additional information as network annotations. We introduce a
network topology modeling framework that treats annotations as an extended
correlation profile of a network. Assuming we have this profile measured for a
given network, we present an algorithm to rescale it in order to construct
networks of varying size that still reproduce the original measured annotation
profile.
Using this methodology, we accurately capture the network properties
essential for realistic simulations of network applications and protocols, or
any other simulations involving complex network topologies, including modeling
and simulation of network evolution. We apply our approach to the Autonomous
System (AS) topology of the Internet annotated with business relationships
between ASs. This topology captures the large-scale structure of the Internet.
In depth understanding of this structure and tools to model it are cornerstones
of research on future Internet architectures and designs. We find that our
techniques are able to accurately capture the structure of annotation
correlations within this topology, thus reproducing a number of its important
properties in synthetically-generated random graphs
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Intra- and Inter-Session Network Coding in Wireless Networks
In this paper, we are interested in improving the performance of constructive
network coding schemes in lossy wireless environments.We propose I2NC - a
cross-layer approach that combines inter-session and intra-session network
coding and has two strengths. First, the error-correcting capabilities of
intra-session network coding make our scheme resilient to loss. Second,
redundancy allows intermediate nodes to operate without knowledge of the
decoding buffers of their neighbors. Based only on the knowledge of the loss
rates on the direct and overhearing links, intermediate nodes can make
decisions for both intra-session (i.e., how much redundancy to add in each
flow) and inter-session (i.e., what percentage of flows to code together)
coding. Our approach is grounded on a network utility maximization (NUM)
formulation of the problem. We propose two practical schemes, I2NC-state and
I2NC-stateless, which mimic the structure of the NUM optimal solution. We also
address the interaction of our approach with the transport layer. We
demonstrate the benefits of our schemes through simulations
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