1,901 research outputs found
Passive available bandwidth: Applying self -induced congestion analysis of application-generated traffic
Monitoring end-to-end available bandwidth is critical in helping applications and users efficiently use network resources. Because the performance of distributed systems is intrinsically linked to the performance of the network, applications that have knowledge of the available bandwidth can adapt to changing network conditions and optimize their performance. A well-designed available bandwidth tool should be easily deployable and non-intrusive. While several tools have been created to actively measure the end-to-end available bandwidth of a network path, they require instrumentation at both ends of the path, and the traffic injected by these tools may affect the performance of other applications on the path.;We propose a new passive monitoring system that accurately measures available bandwidth by applying self-induced congestion analysis to traces of application-generated traffic. The Watching Resources from the Edge of the Network (Wren) system transparently provides available bandwidth information to applications without having to modify the applications to make the measurements and with negligible impact on the performance of applications. Wren produces a series of real-time available bandwidth measurements that can be used by applications to adapt their runtime behavior to optimize performance or that can be sent to a central monitoring system for use by other or future applications.;Most active bandwidth tools rely on adjustments to the sending rate of packets to infer the available bandwidth. The major obstacle with using passive kernel-level traces of TCP traffic is that we have no control over the traffic pattern. We demonstrate that there is enough natural variability in the sending rates of TCP traffic that techniques used by active tools can be applied to traces of application-generated traffic to yield accurate available bandwidth measurements.;Wren uses kernel-level instrumentation to collect traces of application traffic and analyzes the traces in the user-level to achieve the necessary accuracy and avoid intrusiveness. We introduce new passive bandwidth algorithms based on the principles of the active tools to measure available bandwidth, investigate the effectiveness of these new algorithms, implement a real-time system capable of efficiently monitoring available bandwidth, and demonstrate that applications can use Wren measurements to adapt their runtime decisions
Why (and How) Networks Should Run Themselves
The proliferation of networked devices, systems, and applications that we
depend on every day makes managing networks more important than ever. The
increasing security, availability, and performance demands of these
applications suggest that these increasingly difficult network management
problems be solved in real time, across a complex web of interacting protocols
and systems. Alas, just as the importance of network management has increased,
the network has grown so complex that it is seemingly unmanageable. In this new
era, network management requires a fundamentally new approach. Instead of
optimizations based on closed-form analysis of individual protocols, network
operators need data-driven, machine-learning-based models of end-to-end and
application performance based on high-level policy goals and a holistic view of
the underlying components. Instead of anomaly detection algorithms that operate
on offline analysis of network traces, operators need classification and
detection algorithms that can make real-time, closed-loop decisions. Networks
should learn to drive themselves. This paper explores this concept, discussing
how we might attain this ambitious goal by more closely coupling measurement
with real-time control and by relying on learning for inference and prediction
about a networked application or system, as opposed to closed-form analysis of
individual protocols
A traffic classification method using machine learning algorithm
Applying concepts of attack investigation in IT industry, this idea has been developed to design
a Traffic Classification Method using Data Mining techniques at the intersection of Machine
Learning Algorithm, Which will classify the normal and malicious traffic. This classification will
help to learn about the unknown attacks faced by IT industry. The notion of traffic classification
is not a new concept; plenty of work has been done to classify the network traffic for
heterogeneous application nowadays. Existing techniques such as (payload based, port based
and statistical based) have their own pros and cons which will be discussed in this
literature later, but classification using Machine Learning techniques is still an open field to explore and has provided very promising results up till now
Optimization flow control -- I: Basic algorithm and convergence
We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using a gradient projection algorithm. In this system, sources select transmission rates that maximize their own benefits, utility minus bandwidth cost, and network links adjust bandwidth prices to coordinate the sources' decisions. We allow feedback delays to be different, substantial, and time varying, and links and sources to update at different times and with different frequencies. We provide asynchronous distributed algorithms and prove their convergence in a static environment. We present measurements obtained from a preliminary prototype to illustrate the convergence of the algorithm in a slowly time-varying environment. We discuss its fairness property
Network emulation focusing on QoS-Oriented satellite communication
This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication
Controlo de congestionamento em redes sem fios
Doutoramento em Engenharia ElectrotécnicaCongestion control in wireless networks is an important and open issue.
Previous research has proven the poor performance of the Transport
Control Protocol (TCP) in such networks. The factors that contribute
to the poor performance of TCP in wireless environments concern its
unsuitability to identify/detect and react properly to network events,
its TCP window based
ow control algorithm that is not suitable for
the wireless channel, and the congestion collapse due to mobility. New
rate based mechanisms have been proposed to mitigate TCP performance
in wired and wireless networks. However, these mechanisms
also present poor performance, as they lack of suitable bandwidth estimation
techniques for multi-hop wireless networks.
It is thus important to improve congestion control performance in wireless
networks, incorporating components that are suitable for wireless
environments. A congestion control scheme which provides an e -
cient and fair sharing of the underlying network capacity and available
bandwidth among multiple competing applications is crucial to the definition
of new e cient and fair congestion control schemes on wireless
multi-hop networks.
The Thesis is divided in three parts. First, we present a performance
evaluation study of several congestion control protocols against TCP,
in wireless mesh and ad-hoc networks. The obtained results show that
rate based congestion control protocols need an eficient and accurate
underlying available bandwidth estimation technique. The second part
of the Thesis presents a new link capacity and available bandwidth estimation
mechanism denoted as rt-Winf (real time wireless inference).
The estimation is performed in real-time and without the need to intrusively
inject packets in the network. Simulation results show that
rt-Winf obtains the available bandwidth and capacity estimation with
accuracy and without introducing overhead trafic in the network.
The third part of the Thesis proposes the development of new congestion
control mechanisms to address the congestion control problems
of wireless networks. These congestion control mechanisms use cross
layer information, obtained by rt-Winf, to accurately and eficiently estimate
the available bandwidth and the path capacity over a wireless
network path. Evaluation of these new proposed mechanisms, through
ns-2 simulations, shows that the cooperation between rt-Winf and the
congestion control algorithms is able to significantly increase congestion
control eficiency and network performance.O controlo de congestionamento continua a ser extremamente importante
quando se investiga o desempenho das redes sem fios. Trabalhos
anteriores mostram o mau desempenho do Transport Control Proto-
col (TCP) em redes sem fios. Os fatores que contribuem para um
pior desempenho do TCP nesse tipo de redes s~ao: a sua falta de capacidade
para identificar/detetar e reagir adequadamente a eventos da
rede; a utilização de um algoritmo de controlo de
uxo que não é adequado
para o canal sem fios; e o colapso de congestionamento devido
á mobilidade. Para colmatar este problemas foram propostos novos
mecanismos de controlo de congestionamento baseados na taxa de
transmissão. No entanto, estes mecanismos também apresentam um
pior desempenho em redes sem fios, já que não utilizam mecanismos
adequados para a avaliação da largura de banda disponível. Assim, é
importante para melhorar o desempenho do controlo de congestionamento
em redes sem fios, incluir componentes que são adequados para
esse tipo de ambientes. Um esquema de controlo de congestionamento
que permita uma partilha eficiente e justa da capacidade da rede e da
largura de banda disponível entre múltiplas aplicações concorrentes é
crucial para a definição de novos, eficientes e justos mecanismos de
controlo congestionamento para as redes sem fios.
A Tese está dividida em três partes. Primeiro, apresentamos um estudo
sobre a avaliação de desempenho de vários protocolos de controlo de
congestionamento relativamente ao TCP, em redes sem fios em malha
e ad-hoc. Os resultados obtidos mostram que os protocolos baseados
na taxa de transmissão precisam de uma técnica de avaliação da largura
de banda disponível que seja eficiente e precisa . A segunda parte da
Tese apresenta um novo mecanismo de avaliação da capacidade da
ligação e da largura de banda disponível, designada por rt-Winf (real
time wireless inference). A avaliação é realizada em tempo real e sem
a necessidade de inserir tráfego na rede. Os resultados obtidos através
de simulação e emulação mostram que o rt-Winf obtém com precisão
a largura de banda disponível e a capacidade da ligação sem sobrecarregar
a rede. A terceira parte da Tese propõe novos mecanismos de
controlo de congestionamento em redes sem fios. Estes mecanismos
de controlo de congestionamento apresentam um conjunto de caracter
ísticas novas para melhorar o seu desempenho, de entre as quais
se destaca a utilização da informação de largura de banda disponível
obtida pelo rt-Winf. Os resultados da avaliação destes mecanismos,
utilizando o simulador ns-2, permitem concluir que a cooperação entre
o rt-Winf e os algoritmos de controlo de congestionamento aumenta
significativamente o desempenho da rede
Delay-oriented active queue management in TCP/IP networks
PhDInternet-based applications and services are pervading everyday life. Moreover, the growing
popularity of real-time, time-critical and mission-critical applications set new challenges to
the Internet community. The requirement for reducing response time, and therefore latency
control is increasingly emphasized.
This thesis seeks to reduce queueing delay through active queue management. While
mathematical studies and research simulations reveal that complex trade-off relationships
exist among performance indices such as throughput, packet loss ratio and delay, etc., this
thesis intends to find an improved active queue management algorithm which emphasizes
delay control without trading much on other performance indices such as throughput and
packet loss ratio.
The thesis observes that in TCP/IP network, packet loss ratio is a major reflection of
congestion severity or load. With a properly functioning active queue management algorithm,
traffic load will in general push the feedback system to an equilibrium point in terms of
packet loss ratio and throughput. On the other hand, queue length is a determinant factor on
system delay performance while has only a slight influence on the equilibrium. This
observation suggests the possibility of reducing delay while maintaining throughput and
packet loss ratio relatively unchanged.
The thesis also observes that queue length fluctuation is a reflection of both load changes and
natural fluctuation in arriving bit rate. Monitoring queue length fluctuation alone cannot
distinguish the difference and identify congestion status; and yet identifying this difference is
crucial in finding out situations where average queue size and hence queueing delay can be
properly controlled and reasonably reduced. However, many existing active queue
management algorithms only monitor queue length, and their control policies are solely
based on this measurement. In our studies, our novel finding is that the arriving bit rate
distribution of all sources contains information which can be a better indication of
congestion status and has a correlation with traffic burstiness. And this thesis develops a
simple and scalable way to measure its two most important characteristics, namely the mean
ii
and the variance of the arriving rate distribution. The measuring mechanism is based on a
Zombie List mechanism originally proposed and deployed in Stabilized RED to estimate the
number of flows and identify misbehaving flows. This thesis modifies the original zombie
list measuring mechanism, makes it capable of measuring additional variables. Based on
these additional measurements, this thesis proposes a novel modification to the RED
algorithm. It utilizes a robust adaptive mechanism to ensure that the system reaches proper
equilibrium operating points in terms of packet loss ratio and queueing delay under various
loads. Furthermore, it identifies different congestion status where traffic is less bursty and
adapts RED parameters in order to reduce average queue size and hence queueing delay
accordingly.
Using ns-2 simulation platform, this thesis runs simulations of a single bottleneck link
scenario which represents an important and popular application scenario such as home
access network or SoHo. Simulation results indicate that there are complex trade-off
relationships among throughput, packet loss ratio and delay; and in these relationships delay
can be substantially reduced whereas trade-offs on throughput and packet loss ratio are
negligible. Simulation results show that our proposed active queue management algorithm
can identify circumstances where traffic is less bursty and actively reduce queueing delay
with hardly noticeable sacrifice on throughput and packet loss ratio performances.
In conclusion, our novel approach enables the application of adaptive techniques to more
RED parameters including those affecting queue occupancy and hence queueing delay. The
new modification to RED algorithm is a scalable approach and does not introduce additional
protocol overhead. In general it brings the benefit of substantially reduced delay at the cost
of limited processing overhead and negligible degradation in throughput and packet loss
ratio. However, our new algorithm is only tested on responsive flows and a single bottleneck
scenario. Its effectiveness on a combination of responsive and non-responsive flows as well
as in more complicated network topology scenarios is left for future work
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