Some Active Queue Management Methods for Controlling Packet Queueing Delay. Design and Performance Evaluation of Some New Versions of Active Queue Management Schemes for Controlling Packet Queueing Delay in a Buffer to Satisfy Quality of Service Requirements for Real-time Multimedia Applications.
AuthorMohamed, Mahmud H. Etbega
SupervisorWoodward, Mike E.
KeywordActive queue management (AQM) mechanisms
Quality of Service (QoS)
Packet queueing delay
Real-time multimedia applications
Rights© 2009 Mohamed M. H. E. This work is licensed under a Creative Commons Attribution-Non-Commercial-Share-Alike License (http://creativecommons.org/licenses/by-nc-nd/2.0/uk).
InstitutionUniversity of Bradford
DepartmentDepartment of Computing
MetadataShow full item record
AbstractTraditionally the Internet is used for the following applications: FTP, e-mail and Web traffic. However in the recent years the Internet is increasingly supporting emerging applications such as IP telephony, video conferencing and online games. These new applications have different requirements in terms of throughput and delay than traditional applications. For example, interactive multimedia applications, unlike traditional applications, have more strict delay constraints and less strict loss constraints. Unfortunately, the current Internet offers only a best-effort service to all applications without any consideration to the applications specific requirements. In this thesis three existing Active Queue Management (AQM) mechanisms are modified by incorporating into these a control function to condition routers for better Quality of Service (QoS). Specifically, delay is considered as the key QoS metric as it is the most important metric for real-time multimedia applications. The first modified mechanism is Drop Tail (DT), which is a simple mechanism in comparison with most AQM schemes. A dynamic threshold has been added to DT in order to maintain packet queueing delay at a specified value. The modified mechanism is referred to as Adaptive Drop Tail (ADT). The second mechanism considered is Early Random Drop (ERD) and, iii in a similar way to ADT, a dynamic threshold has been used to keep the delay at a required value, the main difference being that packets are now dropped probabilistically before the queue reaches full capacity. This mechanism is referred to as Adaptive Early Random Drop (AERD). The final mechanism considered is motivated by the well known Random Early Detection AQM mechanism and is effectively a multi-threshold version of AERD in which packets are dropped with a linear function between the two thresholds and the second threshold is moveable in order to change the slope of the dropping function. This mechanism is called Multi Threshold Adaptive Early Random Drop (MTAERD) and is used in a similar way to the other mechanisms to maintain delay around a specified level. The main focus with all the mechanisms is on queueing delay, which is a significant component of end-to-end delay, and also on reducing the jitter (delay variation) A control algorithm is developed using an analytical model that specifies the delay as a function of the queue threshold position and this function has been used in a simulation to adjust the threshold to an effective value to maintain the delay around a specified value as the packet arrival rate changes over time. iv A two state Markov Modulated Poisson Process is used as the arrival process to each of the three systems to introduce burstiness and correlation of the packet inter-arrival times and to present sudden changes in the arrival process as might be encountered when TCP is used as the transport protocol and step changes the size of its congestion window. In the investigations it is assumed the traffic source is a mixture of TCP and UDP traffic and that the mechanisms conserved apply to the TCP based data. It is also assumed that this consists of the majority proportion of the total traffic so that the control mechanisms have a significant effect on controlling the overall delay. The three mechanisms are evaluated using a Java framework and results are presented showing the amount of improvement in QoS that can be achieved by the mechanisms over their non-adaptive counterparts. The mechanisms are also compared with each other and conclusions drawn.
Showing items related by title, author, creator and subject.
Control of queueing delay in a buffer with time-varying arrival rate.Awan, Irfan U.; Guan, Lin; Woodward, Mike E. (2006)Quality of Service (QoS) is of extreme importance in accommodating the increasingly diverse range of services and types of traffic in present day communication networks and delay is one of the most important QoS metrics. This paper presents a new approach for constraining queueing delay in a buffer to a specified level as the arrival rate changes with time. A discrete-time control algorithm is presented that operates on a buffer (queue) which incorporates a moveable threshold. An algorithm is developed that controls the delay by dynamically adjusting the threshold which, in turn, controls the arrival rate. The feasibility of the system is examined using both theoretical analysis and simulation.
Entropy Maximisation and Queues With or Without Balking. An investigation into the impact of generalised maximum entropy solutions on the study of queues with or without arrival balking and their applications to congestion management in communication networks.Kouvatsos, Demetres D.; Fretwell, Rod J.; Shah, Neelkamal P. (University of BradfordFaculty of Engineering and Informatics, School of Electrical Engineering and Computer Science, 2015-12-07)An investigation into the impact of generalised maximum entropy solutions on the study of queues with or without arrival balking and their applications to congestion management in communication networks Keywords: Queues, Balking, Maximum Entropy (ME) Principle, Global Balance (GB), Queue Length Distribution (QLD), Generalised Geometric (GGeo), Generalised Exponential (GE), Generalised Discrete Half Normal (GdHN), Congestion Management, Packet Dropping Policy (PDP) Generalisations to links between discrete least biased (i.e. maximum entropy (ME)) distribution inferences and Markov chains are conjectured towards the performance modelling, analysis and prediction of general, single server queues with or without arrival balking. New ME solutions, namely the generalised discrete Half Normal (GdHN) and truncated GdHN (GdHNT) distributions are characterised, subject to appropriate mean value constraints, for inferences of stationary discrete state probability distributions. Moreover, a closed form global balance (GB) solution is derived for the queue length distribution (QLD) of the M/GE/1/K queue subject to extended Morse balking, characterised by a Poisson prospective arrival process, i.i.d. generalised exponential (GE) service times and finite capacity, K. In this context, based on comprehensive numerical experimentation, the latter GB solution is conjectured to be a special case of the GdHNT ME distribution. ii Owing to the appropriate operational properties of the M/GE/1/K queue subject to extended Morse balking, this queueing system is applied as an ME performance model of Internet Protocol (IP)-based communication network nodes featuring static or dynamic packet dropping congestion management schemes. A performance evaluation study in terms of the model’s delay is carried out. Subsequently, the QLD’s of the GE/GE/1/K censored queue subject to extended Morse balking under three different composite batch balking and batch blocking policies are solved via the technique of GB. Following comprehensive numerical experimentation, the latter QLD’s are also conjectured to be special cases of the GdHNT. Limitations of this work and open problems which have arisen are included after the conclusions
A discrete-time performance model for congestion control mechanism using queue thresholds with QOS constraintsGuan, Lin; Woodward, Mike E.; Awan, Irfan U. (2005)This paper presents a new analytical framework for the congestion control of Internet traffic using a queue threshold scheme. This framework includes two discrete-time analytical models for the performance evaluation of a threshold based congestion control mechanism and compares performance measurements through typical numerical results. To satisfy the low delay along with high throughput, model-I incorporates one threshold to make the arrival process step reduce from arrival rate ¿1 directly to ¿2 once the number of packets in the system has reached the threshold value L1. The source operates normally, otherwise. Model-II incorporates two thresholds to make the arrival rate linearly reduce from ¿1 to ¿2 with system contents when the number of packets in the system is between two thresholds L1 and L2. The source operates normally with arrival rate ¿1 before threshold L1, and with arrival rate ¿2 after the threshold L2. In both performance models, the mean packet delay W, probability of packet loss PL and throughput S have been found as functions of the thresholds and maximum drop probability. The performance comparison results for the two models have also been made through typical numerical results. The results clearly demonstrate how different load settings can provide different tradeoffs between throughput, loss probability and delay to suit different service requirements.