Congestion control and QoS provisioning in IP networks.

Hua Cunqing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.Includes bibliographical references (leaves 53-56).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Congestion Control in the IP Network --- p.1Chapter 1.2 --- Quality of Service in the IP network --- p.2Chapter 1.3 --- Structure of Thesis --- p.3Chapter 2 --- Background --- p.4Chapter 2.1 --- TCP and Congestion Control --- p.4Chapter 2.1.1 --- Slow Start --- p.4Chapter 2.1.2 --- Congestion Avoidance --- p.5Chapter 2.1.3 --- "Fast Retransmit, Fast Recovery and Timeout" --- p.5Chapter 2.2 --- Active Queue Management --- p.7Chapter 2.3 --- Integrated Services and Differentiated Services --- p.8Chapter 3 --- The Fairness of TCP Vegas in Networks with Multiple Congested Gate- ways --- p.10Chapter 3.1 --- Introduction --- p.10Chapter 3.2 --- TCP Vegas and related works --- p.11Chapter 3.3 --- Analysis --- p.13Chapter 3.4 --- Simulation Results --- p.15Chapter 3.4.1 --- Throughput for different number of active cross connections --- p.16Chapter 3.4.2 --- Throughput for different number of flows in each connection --- p.17Chapter 3.4.3 --- Multiple congestion vs Single congestion --- p.17Chapter 3.5 --- Summary --- p.19Chapter 4 --- The Joint Congestion Control for TCP/IP Networks --- p.21Chapter 4.1 --- Background --- p.21Chapter 4.2 --- The Joint Congestion Control --- p.23Chapter 4.2.1 --- Path Load Reduction Factor --- p.23Chapter 4.2.2 --- The Congestion Control Algorithm --- p.24Chapter 4.2.3 --- Probing Interval --- p.26Chapter 4.2.4 --- Parameter Setting --- p.26Chapter 4.2.5 --- Encoding of R --- p.27Chapter 4.3 --- Simulation Results --- p.28Chapter 4.3.1 --- Congestion Window Behavior --- p.28Chapter 4.3.2 --- Throughput Stability --- p.31Chapter 4.3.3 --- Packet Loss Ratio --- p.31Chapter 4.3.4 --- Fairness Index --- p.32Chapter 4.3.5 --- Fairness in Multiple-hop Network --- p.32Chapter 4.3.6 --- Parameter Sensitivity --- p.33Chapter 4.3.7 --- Interaction between JCC and Reno flows --- p.35Chapter 4.4 --- Summary --- p.35Chapter 5 --- S-WTP : Shifted Waiting Time Priority Scheduling for Delay Differ- entiated Services --- p.37Chapter 5.1 --- Introduction --- p.37Chapter 5.2 --- Scheduling Algorithms for Delay Differentiated Services --- p.38Chapter 5.3 --- Shifted Waiting Time Priority Scheduling --- p.41Chapter 5.3.1 --- Local Update --- p.42Chapter 5.3.2 --- Global Update --- p.42Chapter 5.3.3 --- Computational overhead --- p.42Chapter 5.4 --- Simulation Results --- p.43Chapter 5.4.1 --- Microscopic View of Individual Packet Delay of S-WTP and WTP --- p.43Chapter 5.4.2 --- Delay Ratios in Different Timescales --- p.44Chapter 5.4.3 --- Effects of aggregate traffic and class load distribution on delay ratio --- p.44Chapter 5.4.4 --- Delay Ratios with More Classes --- p.48Chapter 5.5 --- Summary --- p.48Chapter 6 --- Conclusions --- p.50Chapter 6.1 --- Congestion Control --- p.50Chapter 6.2 --- Quality of Service Provision --- p.51Chapter 6.3 --- Final Remarks --- p.5

Improved congestion control for packet switched data networks and the Internet

Congestion control is one of the fundamental issues in computer networks. Without proper congestion control mechanisms there is the possibility of inefficient utilization of resources, ultimately leading to network collapse. Hence congestion control is an effort to adapt the performance of a network to changes in the traffic load without adversely affecting users perceived utilities. This thesis is a step in the direction of improved network congestion control. Traditionally the Internet has adopted a best effort policy while relying on an end-to-end mechanism. Complex functions are implemented by end users, keeping the core routers of network simple and scalable. This policy also helps in updating the software at the users' end. Thus, currently most of the functionality of the current Internet lie within the end users' protocols, particularly within Transmission Control Protocol (TCP). This strategy has worked fine to date, but networks have evolved and the traffic volume has increased many fold; hence routers need to be involved in controlling traffic, particularly during periods of congestion. Other benefits of using routers to control the flow of traffic would be facilitating the introduction of differentiated services or offering different qualities of service to different users. Any real congestion episode due to demand of greater than available bandwidth, or congestion created on a particular target host by computer viruses, will hamper the smooth execution of the offered network services. Thus, the role of congestion control mechanisms in modern computer networks is very crucial. In order to find effective solutions to congestion control, in this thesis we use feedback control system models of computer networks. The closed loop formed by TCPIIP between the end hosts, through intermediate routers, relies on implicit feedback of congestion information through returning acknowledgements. This feedback information about the congestion state of the network can be in the form of lost packets, changes in round trip time and rate of arrival of acknowledgements. Thus, end hosts can either execute reactive or proactive congestion control mechanisms. The former approach uses duplicate acknowledgements and timeouts as congestion signals, as done in TCP Reno, whereas the latter approach depends on changes in the round trip time, as in TCP Vegas. The protocols employing the second approach are still in their infancy as they cannot co-exist safely with protocols employing the first approach. Whereas TCP Reno and its mutations, such as TCP Sack, are presently widely used in computer networks, including the current Internet. These protocols require packet losses to happen before they can detect congestion, thus inherently leading to wastage of time and network bandwidth. Active Queue Management (AQM) is an alternative approach which provides congestion feedback from routers to end users. It makes a network to behave as a sensitive closed loop feedback control system, with a response time of one round trip time, congestion information being delivered to the end host to reduce data sending rates before actual packets losses happen. From this congestion information, end hosts can reduce their congestion window size, thus pumping fewer packets into a congested network until the congestion period is over and routers stop sending congestion signals. Keeping both approaches in view, we have adopted a two-pronged strategy to address the problem of congestion control. They are to adapt the network at its edges as well as its core routers. We begin by introducing TCPIIP based computer networks and defining the congestion control problem. Next we look at different proactive end-to-end protocols, including TCP Vegas due to its better fairness properties. We address the incompatibility problem between TCP Vegas and TCP Reno by using ECN based on Random Early Detection (RED) algorithm to adjust parameters of TCP Vegas. Further, we develop two alternative algorithms, namely optimal minimum variance and generalized optimal minimum variance, for fair end-to-end protocols. The relationship between (p, 1) proportionally fair algorithm and the generalized algorithm is investigated along with conditions for its stable operation. Noteworthy is a novel treatment of the issue of transient fairness. This represents the work done on congestion control at the edges of network. Next, we focus on router-based congestion control algorithms and start with a survey of previous work done in that direction. We select the RED algorithm for further work due to it being recommended for the implementation of AQM. First we devise a new Hybrid RED algorithm which employs instantaneous queue size along with an exponential weighted moving average queue size for making decisions about packet marking/dropping, and adjusts the average value during periods of low traffic. This algorithm improves the link utilization and packet loss rate as compared to basic RED. We further propose a control theory based Auto-tuning RED algorithm that adapts to changing traffic load. This algorithm can clamp the average queue size to a desired reference value which can be used to estimate queuing delays for Quality of Service purposes. As an alternative approach to router-based congestion control, we investigate Proportional, Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) principles based control algorithms for AQM. New control-theoretic RED and frequency response based PI and PID control algorithms are developed and their performance is compared with that of existing algorithms. Later we transform the RED and PI principle based algorithms into their adaptive versions using the well known square root of p formula. The performance of these load adaptive algorithms is compared with that of the previously developed fixed parameter algorithms. Apart from some recent research, most of the previous efforts on the design of congestion control algorithms have been heuristic. This thesis provides an effective use of control theory principles in the design of congestion control algorithms. We develop fixed-parameter-type feedback congestion control algorithms as well as their adaptive versions. All of the newly proposed algorithms are evaluated by using ns-based simulations. The thesis concludes with a number of research proposals emanating from the work reported

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

Actas da 10ª Conferência sobre Redes de Computadores

Universidade do MinhoCCTCCentro AlgoritmiCisco SystemsIEEE Portugal Sectio

1995 BRAC Commission

Executive Correspondence Tracking System #13 - April 1995 (950420-10 TO 95425-17). Box 52, C-108