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Performance modelling of a multiple threshold RED mechanism for bursty and correlated Internet traffic with MMPP arrival process
Access to the large web content hosted all over the world by users of the Internet engage
many hosts, routers/switches and faster links. They challenge the internet backbone to operate at
its capacity to assure e±cient content access. This may result in congestion and raises concerns over
various Quality of Service (QoS) issues like high delays, high packet loss and low throughput of the
system for various Internet applications. Thus, there is a need to develop effective congestion control
mechanisms in order to meet various Quality of Service (QoS) related performance parameters. In this
paper, our emphasis is on the Active Queue Management (AQM) mechanisms, particularly Random
Early Detection (RED). We propose a threshold based novel analytical model based on standard RED
mechanism. Various numerical examples are presented for Internet traffic scenarios containing both the
burstiness and correlation properties of the network traffic
Reduction of queue oscillation in the next generation Internet routers
The Internet routers employing the random early detection (RED) algorithm for congestion control suffer from the problem of chaotic queue oscillation. It is well known that the slowly varying nature of the average queue size computed using an exponentially weighted moving average (EWMA) used in the RED scheme causes this chaotic behavior. This paper presents a new mathematical function to model the weighting parameter used in the EWMA. The proposed weighting function incorporates the knowledge of the dynamic changes in the congestion characteristics, traffic characteristics and queue normalization. Using this pragmatic information eliminates the slowly varying nature of the average queue size. It is evident from our simulations that the proposed approach not only reduces the chaotic queue oscillation significantly but also provides predictable low delay and low delay jitter with high throughput gain and reduced packet loss rate even under heavy load of traffic conditions
TCP – Random Early Detection (RED) mechanism for Congestion Control
This thesis discusses the Random Early Detection (RED) algorithm, proposed by Sally Floyd, used for congestion avoidance in computer networking, how existing algorithms compare to this approach and the configuration and implementation of the Weighted Random Early Detection (WRED) variation.
RED uses a probability approach in order to calculate the probability that a packet will be dropped before periods of high congestion, relative to the minimum and maximum queue threshold, average queue length, packet size and the number of packets since the last drop.
The motivation for this thesis has been the high QoS provided to current delay-sensitive applications such as Voice-over-IP (VoIP) by the incorporation of congestion avoidance algorithms derived from the original RED design [45]. The WRED variation of RED is not directly invoked on the VoIP class because congestion avoidance mechanisms are not configured for voice queues. WRED is instead used to prioritize other traffic classes in order to avoid congestion to provide and guarantee high quality of service for voice traffic [43][44].
The most notable simulations performed for the RED algorithm in comparison to the Tail Drop (TD) and Random Drop (RD) algorithms have been detailed in order to show that RED is much more advantageous in terms of congestion control in a network. The WRED, Flow RED (FRED) and Adaptive RED (ARED) variations of the RED algorithm have been detailed with emphasis on WRED. Details of the concepts of forwarding classes, output queues, traffic policies, traffic classes, class maps, schedulers, scheduler maps, and DSCP classification shows that the WRED feature is easily configurable on tier-1 vendor routers
Controlling Network Latency in Mixed Hadoop Clusters: Do We Need Active Queue Management?
With the advent of big data, data center applications are processing vast amounts of unstructured and semi-structured data, in parallel on large clusters, across hundreds to thousands of nodes. The highest performance for these batch big data workloads is achieved using expensive network equipment with large buffers, which accommodate bursts in network traffic and allocate bandwidth fairly even when the network is congested. Throughput-sensitive big data applications are, however, often executed in the same data center as latency-sensitive workloads. For both workloads to be supported well, the network must provide both maximum throughput and low latency. Progress has been made in this direction, as modern network switches support Active Queue Management (AQM) and Explicit Congestion Notifications (ECN), both mechanisms to control the level of queue occupancy, reducing the total network latency. This paper is the first study of the effect of Active Queue Management on both throughput and latency, in the context of Hadoop and the MapReduce programming model. We give a quantitative comparison of four different approaches for controlling buffer occupancy and latency: RED and CoDel, both standalone and also combined with ECN and DCTCP network protocol, and identify the AQM configurations that maintain Hadoop execution time gains from larger buffers within 5%, while reducing network packet latency caused by bufferbloat by up to 85%. Finally, we provide recommendations to administrators of Hadoop clusters as to how to improve latency without degrading the throughput of batch big data workloads.The research leading to these results has received funding from the European Unions Seventh Framework Programme (FP7/2007–2013) under grant agreement number 610456 (Euroserver).
The research was also supported by the Ministry of Economy and Competitiveness of Spain under the contracts TIN2012-34557 and TIN2015-65316-P, Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272), HiPEAC-3 Network of Excellence (ICT- 287759), and the Severo Ochoa Program (SEV-2011-00067) of the Spanish Government.Peer ReviewedPostprint (author's final draft
Optimizing Service Differentiation Scheme with Sized-based Queue Management in DiffServ Networks
In this paper we introduced Modified Sized-based Queue Management as a
dropping scheme that aims to fairly prioritize and allocate more service to
VoIP traffic over bulk data like FTP as the former one usually has small packet
size with less impact to the network congestion. In the same time, we want to
guarantee that this prioritization is fair enough for both traffic types. On
the other hand we study the total link delay over the congestive link with the
attempt to alleviate this congestion as much as possible at the by function of
early congestion notification. Our M-SQM scheme has been evaluated with NS2
experiments to measure the packets received from both and total link-delay for
different traffic. The performance evaluation results of M-SQM have been
validated and graphically compared with the performance of other three legacy
AQMs (RED, RIO, and PI). It is depicted that our M-SQM outperformed these AQMs
in providing QoS level of service differentiation.Comment: 10 pages, 9 figures, 1 table, Submitted to Journal of
Telecommunication
The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena
The Internet is the most complex system ever created in human history.
Therefore, its dynamics and traffic unsurprisingly take on a rich variety of
complex dynamics, self-organization, and other phenomena that have been
researched for years. This paper is a review of the complex dynamics of
Internet traffic. Departing from normal treatises, we will take a view from
both the network engineering and physics perspectives showing the strengths and
weaknesses as well as insights of both. In addition, many less covered
phenomena such as traffic oscillations, large-scale effects of worm traffic,
and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex
System
Operational and Performance Issues of a CBQ router
The use of scheduling mechanisms like Class Based Queueing (CBQ) is expected to play a key role in next generation multiservice IP networks. In this paper we attempt an experimental evaluation of ALTQ/CBQ demonstrating its sensitivity to a wide range of parameters and link layer driver design issues. We pay attention to several CBQ internal parameters that affect performance drastically and particularly to “borrowing”, a key feature for flexible and efficient link sharing. We are also investigating cases where the link sharing rules are violated, explaining and correcting these effects wheneverpossible. Finally we evaluateCBQ performance and make suggestions for effective deployment in real networks.
Discrete-time queueing model for responsive network traffic and bottleneck queues
The Internet has been more and more intensively used in recent years. Although network infrastructure has been regularly upgraded, and the ability to manage heavy traffic greatly increased, especially on the core networks, congestion never ceases to appear, as the amount of traffic that flow on the Internet seems to be increasing at an even faster rate. Thus, congestion control mechanisms play a vital role in the functioning of the Internet. Active Queue Management (AQM) is a popular type of congestion control mechanism that is implemented on gateways (most notably routers), which can predict and avoid the congestion before it happens. When properly configured, AQMs can effectively reduce the congestion, and alleviate some of the problems such as global synchronisation and unfairness to bursty traffic.
However, there are still many problems regarding AQMs. Most of the AQM schemes are quite sensitive to their parameters setting, and these parameters may be heavily dependent on the network traffic profile, which the administrator may not have intensive knowledge of, and is likely to change over time. When poorly configured, many AQMs perform no better than the basic drop-tail queue. There is currently no effective method to compare the performance of these AQM algorithms, caused by the parameter configuration problem.
In this research, the aim is to propose a new analytical model, which mainly uses discrete-time queueing theory. A novel transient modification to the conventional equilibrium-based method is proposed, and it is utilised to further develop a dynamic interactive model of responsive traffic and bottleneck queues. Using step-by-step analysis, it represents the bursty traffic and oscillating queue length behaviour in practical network more accurately. It also provides an effective way of predicting the behaviour of a TCP-AQM system, allowing easier parameter optimisation for AQM schemes. Numerical solution using MATLAB and software simulation using NS-2 are used to extensively validate the proposed models, theories and conclusions
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