3,149 research outputs found
Increasing resilience of ATM networks using traffic monitoring and automated anomaly analysis
Systematic network monitoring can be the cornerstone for
the dependable operation of safety-critical distributed
systems. In this paper, we present our vision for informed
anomaly detection through network monitoring and
resilience measurements to increase the operators'
visibility of ATM communication networks. We raise the
question of how to determine the optimal level of
automation in this safety-critical context, and we present a
novel passive network monitoring system that can reveal
network utilisation trends and traffic patterns in diverse
timescales. Using network measurements, we derive
resilience metrics and visualisations to enhance the
operators' knowledge of the network and traffic behaviour,
and allow for network planning and provisioning based on
informed what-if analysis
Transport congestion events detection (TCED): towards decorrelating congestion detection from TCP
TCP (Transmission Control Protocol) uses a loss-based algorithm to estimate whether the network is congested or not.
The main difficulty for this algorithm is to distinguish spurious from real network congestion events. Other research studies have proposed to enhance the reliability of this congestion estimation by modifying the internal TCP algorithm.
In this paper, we propose an original congestion event algorithm implemented independently of the TCP source code. Basically, we propose a modular architecture to implement a congestion event detection algorithm to cope with the increasing complexity of the TCP code and we use it to understand why some spurious congestion events might not be
detected in some complex cases. We show that our proposal is able to increase the reliability of TCP NewReno congestion detection algorithm that might help to the design of detection criterion independent of the TCP code. We find out that solutions based only on RTT (Round-Trip Time) estimation are not accurate enough to cover all existing cases.
Furthermore, we evaluate our algorithm with and without network reordering where other inaccuracies, not previously
identified, occur
Network emulation focusing on QoS-Oriented satellite communication
This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication
Self-generated Self-similar Traffic
Self-similarity in the network traffic has been studied from several aspects:
both at the user side and at the network side there are many sources of the
long range dependence. Recently some dynamical origins are also identified: the
TCP adaptive congestion avoidance algorithm itself can produce chaotic and long
range dependent throughput behavior, if the loss rate is very high. In this
paper we show that there is a close connection between the static and dynamic
origins of self-similarity: parallel TCPs can generate the self-similarity
themselves, they can introduce heavily fluctuations into the background traffic
and produce high effective loss rate causing a long range dependent TCP flow,
however, the dropped packet ratio is low.Comment: 8 pages, 12 Postscript figures, accepted in Nonlinear Phenomena in
Complex System
SSthreshless Start: A Sender-Side TCP Intelligence for Long Fat Network
Measurement shows that 85% of TCP flows in the internet are short-lived flows
that stay most of their operation in the TCP startup phase. However, many
previous studies indicate that the traditional TCP Slow Start algorithm does
not perform well, especially in long fat networks. Two obvious problems are
known to impact the Slow Start performance, which are the blind initial setting
of the Slow Start threshold and the aggressive increase of the probing rate
during the startup phase regardless of the buffer sizes along the path. Current
efforts focusing on tuning the Slow Start threshold and/or probing rate during
the startup phase have not been considered very effective, which has prompted
an investigation with a different approach. In this paper, we present a novel
TCP startup method, called threshold-less slow start or SSthreshless Start,
which does not need the Slow Start threshold to operate. Instead, SSthreshless
Start uses the backlog status at bottleneck buffer to adaptively adjust probing
rate which allows better seizing of the available bandwidth. Comparing to the
traditional and other major modified startup methods, our simulation results
show that SSthreshless Start achieves significant performance improvement
during the startup phase. Moreover, SSthreshless Start scales well with a wide
range of buffer size, propagation delay and network bandwidth. Besides, it
shows excellent friendliness when operating simultaneously with the currently
popular TCP NewReno connections.Comment: 25 pages, 10 figures, 7 table
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