70,693 research outputs found
Bandwidth and accuracy-aware state estimation for smart grids using software defined networks
Smart grid (SG) will be one of the major application domains that will present severe pressures on future communication networks due to the expected huge number of devices that will be connected to it and that will impose stringent quality transmission requirements. To address this challenge, there is a need for a joint management of both monitoring and communication systems, so as to achieve a flexible and adaptive management of the SG services. This is the issue addressed in this paper, which provides the following major contributions. We define a new strategy to optimize the accuracy of the state estimation (SE) of the electric grid based on available network bandwidth resources and the sensing intelligent electronic devices (IEDs) installed in the field. In particular, we focus on phasor measurement units (PMUs) as measurement devices. We propose the use of the software defined networks (SDN) technologies to manage the available network bandwidth, which is then assigned by the controller to the forwarding devices to allow for the flowing of the data streams generated by the PMUs, by considering an optimization routine to maximize the accuracy of the resulting SE. Additionally, the use of SDN allows for adding and removing PMUs from the monitoring architecture without any manual intervention. We also provide the details of our implementation of the SDN solution, which is used to make simulations with an IEEE 14-bus test network in order to show performance in terms of bandwidth management and estimation accuracy
Reactive Forwarding and Proactive Forwarding Performance Comparison on SDN-Based Network
Software-defined networking (SDN) technology is one key technology in telecommunications networks that are currently widely studied. In SDN-based networks, the controller holds the key to the reliability of a network because all control functions are held by the controller as one of the open-source controllers, the Open Network Operating System (ONOS) has two forwarding mechanisms, namely reactive forwarding, and proactive forwarding. This study compares performance between reactive forwarding and proactive forwarding on ONOS with VM migration as traffic. The parameter measured is the total migration time using simple network topology. From the test results, the proactive forwarding scenario can optimize the fastest potential of the topology tested by using the path that has the largest bandwidth available on the network topology. In comparison, reactive forwarding can only pass through the smallest hops of the tested topology. From the measurement results, the average migration time performance using a proactive forwarding scenario is 36.16% faster than the reactive forwarding scenario
PBE-CC: Congestion Control via Endpoint-Centric, Physical-Layer Bandwidth Measurements
Wireless networks are becoming ever more sophisticated and overcrowded,
imposing the most delay, jitter, and throughput damage to end-to-end network
flows in today's internet. We therefore argue for fine-grained mobile
endpoint-based wireless measurements to inform a precise congestion control
algorithm through a well-defined API to the mobile's wireless physical layer.
Our proposed congestion control algorithm is based on Physical-Layer Bandwidth
measurements taken at the Endpoint (PBE-CC), and captures the latest 5G New
Radio innovations that increase wireless capacity, yet create abrupt rises and
falls in available wireless capacity that the PBE-CC sender can react to
precisely and very rapidly. We implement a proof-of-concept prototype of the
PBE measurement module on software-defined radios and the PBE sender and
receiver in C. An extensive performance evaluation compares PBE-CC head to head
against the leading cellular-aware and wireless-oblivious congestion control
protocols proposed in the research community and in deployment, in mobile and
static mobile scenarios, and over busy and quiet networks. Results show 6.3%
higher average throughput than BBR, while simultaneously reducing 95th
percentile delay by 1.8x
Network emulation focusing on QoS-Oriented satellite communication
This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication
Time4: Time for SDN
With the rise of Software Defined Networks (SDN), there is growing interest
in dynamic and centralized traffic engineering, where decisions about
forwarding paths are taken dynamically from a network-wide perspective.
Frequent path reconfiguration can significantly improve the network
performance, but should be handled with care, so as to minimize disruptions
that may occur during network updates.
In this paper we introduce Time4, an approach that uses accurate time to
coordinate network updates. Time4 is a powerful tool in softwarized
environments, that can be used for various network update scenarios.
Specifically, we characterize a set of update scenarios called flow swaps, for
which Time4 is the optimal update approach, yielding less packet loss than
existing update approaches. We define the lossless flow allocation problem, and
formally show that in environments with frequent path allocation, scenarios
that require simultaneous changes at multiple network devices are inevitable.
We present the design, implementation, and evaluation of a Time4-enabled
OpenFlow prototype. The prototype is publicly available as open source. Our
work includes an extension to the OpenFlow protocol that has been adopted by
the Open Networking Foundation (ONF), and is now included in OpenFlow 1.5. Our
experimental results show the significant advantages of Time4 compared to other
network update approaches, and demonstrate an SDN use case that is infeasible
without Time4.Comment: This report is an extended version of "Software Defined Networks:
It's About Time", which was accepted to IEEE INFOCOM 2016. A preliminary
version of this report was published in arXiv in May, 201
Multi-path Probabilistic Available Bandwidth Estimation through Bayesian Active Learning
Knowing the largest rate at which data can be sent on an end-to-end path such
that the egress rate is equal to the ingress rate with high probability can be
very practical when choosing transmission rates in video streaming or selecting
peers in peer-to-peer applications. We introduce probabilistic available
bandwidth, which is defined in terms of ingress rates and egress rates of
traffic on a path, rather than in terms of capacity and utilization of the
constituent links of the path like the standard available bandwidth metric. In
this paper, we describe a distributed algorithm, based on a probabilistic
graphical model and Bayesian active learning, for simultaneously estimating the
probabilistic available bandwidth of multiple paths through a network. Our
procedure exploits the fact that each packet train provides information not
only about the path it traverses, but also about any path that shares a link
with the monitored path. Simulations and PlanetLab experiments indicate that
this process can dramatically reduce the number of probes required to generate
accurate estimates
Channel Sounding for the Masses: Low Complexity GNU 802.11b Channel Impulse Response Estimation
New techniques in cross-layer wireless networks are building demand for
ubiquitous channel sounding, that is, the capability to measure channel impulse
response (CIR) with any standard wireless network and node. Towards that goal,
we present a software-defined IEEE 802.11b receiver and CIR estimation system
with little additional computational complexity compared to 802.11b reception
alone. The system implementation, using the universal software radio peripheral
(USRP) and GNU Radio, is described and compared to previous work. By overcoming
computational limitations and performing direct-sequence spread-spectrum
(DS-SS) matched filtering on the USRP, we enable high-quality yet inexpensive
CIR estimation. We validate the channel sounder and present a drive test
campaign which measures hundreds of channels between WiFi access points and an
in-vehicle receiver in urban and suburban areas
Design of a Hybrid Modular Switch
Network Function Virtualization (NFV) shed new light for the design,
deployment, and management of cloud networks. Many network functions such as
firewalls, load balancers, and intrusion detection systems can be virtualized
by servers. However, network operators often have to sacrifice programmability
in order to achieve high throughput, especially at networks' edge where complex
network functions are required.
Here, we design, implement, and evaluate Hybrid Modular Switch (HyMoS). The
hybrid hardware/software switch is designed to meet requirements for modern-day
NFV applications in providing high-throughput, with a high degree of
programmability. HyMoS utilizes P4-compatible Network Interface Cards (NICs),
PCI Express interface and CPU to act as line cards, switch fabric, and fabric
controller respectively. In our implementation of HyMos, PCI Express interface
is turned into a non-blocking switch fabric with a throughput of hundreds of
Gigabits per second.
Compared to existing NFV infrastructure, HyMoS offers modularity in hardware
and software as well as a higher degree of programmability by supporting a
superset of P4 language
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