The drop activation function of the fast congestion notification (FN) mechanism

Fast Congestion Notification (FN) one of the proactive queue management mechanisms that practices congestion avoidance to help avoid the beginning of congestion by marking/dropping packets before the router’s queue gets full; and exercises congestion control, when congestion avoidance fails, by increasing the rate of packet marking/dropping. Upon arrival of each packet, FN uses the instantaneous queue size and the average arrival rate to calculate the packet marking/dropping probability.This paper presents the Drop/Mark Activation Function, which is an internal (built in) function of FN marking/dropping probably function, and shows the conditions under which the FN will trigger a probabilistic packet marking/dropping. This paper shows that the FN’s drop activation function is given by L(Ri, Qcur) =(Ri −μ).T−(Qopt −Qcur)which compares the predicted and required/allowed changes in the queue level, over a time period, to decide whether to attempt or not to attempt packet dropping. L(Ri, Qcur) = 0 defines the set of the drop activation threshold , the set of (average rate, current queue size), (Ri, Qcur), points for which the required/allowed and predicted decrease/increase in the queue level exactly equal each other and that identify the boundary between the drop region (L(Ri, Qcur) > 0), the sets of points at which the packet dropping is attempted, and the no-drop region (L(Ri, Qcur) < 0), the set of points at which the packet dropping is not attempted

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

Traffic Profiles and Performance Modelling of Heterogeneous Networks

This thesis considers the analysis and study of short and long-term traffic patterns of heterogeneous networks. A large number of traffic profiles from different locations and network environments have been determined. The result of the analysis of these patterns has led to a new parameter, namely the 'application signature'. It was found that these signatures manifest themselves in various granularities over time, and are usually unique to an application, permanent virtual circuit (PVC), user or service. The differentiation of the application signatures into different categories creates a foundation for short and long-term management of networks. The thesis therefore looks from the micro and macro perspective on traffic management, covering both aspects. The long-term traffic patterns have been used to develop a novel methodology for network planning and design. As the size and complexity of interconnected systems grow steadily, usually covering different time zones, geographical and political areas, a new methodology has been developed as part of this thesis. A part of the methodology is a new overbooking mechanism, which stands in contrast to existing overbooking methods created by companies like Bell Labs. The new overbooking provides companies with cheaper network design and higher average throughput. In addition, new requirements like risk factors have been incorporated into the methodology, which lay historically outside the design process. A large network service provider has implemented the overbooking mechanism into their network planning process, enabling practical evaluation. The other aspect of the thesis looks at short-term traffic patterns, to analyse how congestion can be controlled. Reoccurring short-term traffic patterns, the application signatures, have been used for this research to develop the "packet train model" further. Through this research a new congestion control mechanism was created to investigate how the application signatures and the "extended packet train model" could be used. To validate the results, a software simulation has been written that executes the proprietary congestion mechanism and the new mechanism for comparison. Application signatures for the TCP/IP protocols have been applied in the simulation and the results are displayed and discussed in the thesis. The findings show the effects that frame relay congestion control mechanisms have on TCP/IP, where the re-sending of segments, buffer allocation, delay and throughput are compared. The results prove that application signatures can be used effectively to enhance existing congestion control mechanisms.AT&T (UK) Ltd, Englan

Congestion Control for Adaptive Satellite Communication Systems with Intelligent Systems

With the advent of life critical and real-time services such as remote operations over satellite, e-health etc, providing the guaranteed minimum level of services at every ground terminal of the satellite communication system has gained utmost priority. Ground terminals and the hub are not equipped with the required intelligence to predict and react to inclement and dynamic weather conditions on its own. The focus of this thesis is to develop intelligent algorithms that would aid in adaptive management of the quality of service at the ground terminal and the gateway level. This is done to adapt both the ground terminal and gateway to changing weather conditions and to attempt to maintain a steady throughput level and Quality of Service (QoS) requirements on queue delay, jitter, and probability of loss of packets. The existing satellite system employs the First-In-First-Out routing algorithm to control congestion in their networks. This mechanism is not equipped with adequate ability to contend with changing link capacities, a common result due to bad weather and faults and to provide different levels of prioritized service to the customers that satisfies QoS requirements. This research proposes to use the reported strength of fuzzy logic in controlling highly non-linear and complex system such as the satellite communication network. The proposed fuzzy based model when integrated into the satellite gateway provides the needed robustness to the ground terminals to comprehend with varying levels of traffic and dynamic impacts of weather

Performance modelling and analysis of congestion control mechanisms for communication networks with quality of service constraints. An investigation into new methods of controlling congestion and mean delay in communication networks with both short range dependent and long range dependent traffic.

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that haveMinistry of Higher Education in Egypt and the Egyptian Cultural Centre and Educational Bureau in Londo

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

An Introduction to Computer Networks

An open textbook for undergraduate and graduate courses on computer networks