A quantitative analysis and performance study of fast congestion notification (FN) mechanism

Congestion in computer network happens when the number of transmission requests exceeds the transmission capacity at a certain network point (called a bottle-neck resource) at a specific time. Congestion usually causes buffers overflow and packets loss. The purpose of congestion management is to maintain a balance between the transmission requests and the transmission capacity so that the bottle-neck resources operate on an optimal level, and the sources are offered service in a way that assures fairness. Fast Congestion Notification (FN) is one of the proactive queue management mechanisms that limits the queuing delay and achieves the maximum link utilization possible with minimum packet drops. In this paper we present a detailed performance comparison of the Linear FN algorithm to RED based on the results obtained through simulations. The paper shows how FN can be tuned for different window size (Ws) and periods of time constant (T) to achieve higher link utilization; reduce the queuing delay, and lower packet drop ratio

Enhanced Queue Management Mechanism for Differentiated Services Networks

In the Internet, it is supposed that all connections are treated equally in the network. Due to the limitation of network resources are limited, providing guarantees on performance measures imposes declining new connections if resources are not available. Assigning network resources to connections according to their classes requires differentiating between the connection classes. For this reason, the Differentiated Services (DiffServ) has been proposed. Many of the QoS mechanisms have been developed which allow different services carried by the Internet to co-exist. Many of these mechanisms were both complex and failed to scale to meet the demands of the Internet. MRED is the common mechanism used in DifJServ routers. It suflers from large queue length variation and untimely congestion detection and notification. These consequences cause performance degradation due to high queuing delays and high packet loss. In this project, enhanced version of MRED is developed to improve the performance of Diffserv networks that use TCP as the transport layer protocol. Enhanced MRED includes average packet arrival rate when computing the packet drop probability. Enhanced MRED showed a good pedonnance compared to that of MRED, in term of fast congestion detection and notification. The limitation of the new mechanism is that it works only with responsive connections which play a big role in avoiding and controlling the congestion. The major contribution of this project is to provide an improved queue management mechanism for Diffserv networks that responds to congestion more quickly, delivers congestion notification timers, and controls the queue length directly to congestion which results in minimizing queue length variation. All these would help improve the DlffServ networks performance

Queue Management Performance Evaluation of REM, GRED, and DropTail Algorithms

As the new user applications and Internet traffic are increased rapidly Rapid growth, the need for developing the Internet infrastructure that guarantee good level of quality of service became necessary. Congestion that is caused by uncontrollable amount of traffic remains as a main problem that threats the Quality of Service (QoS) on the Internet. Proactive Queue Management Mechanisms employed in the Internet routers help in improving the performance of responsive applications such as TCP applications. The selection of Active queue management mechanism plays an important role that leads to well network performance and utilization. In this project, we performance evaluation for examining the performance of the some of the known queue management mechanisms, namely DropTail, REM, and RED proposed for IP routers to achieve performance among competing sources. The purpose of this performance examination is to identify the key parameters to improve the fairness and link utilization in TCP/IP networks. In addition, this will help obtaining a better understanding of these mechanisms by identifying and clarifying factors that influence their performance in order to improve TCP/IP networks performance overall

A conceptual architecture for adaptation in remote desktop systems driven by the user perception of multimedia

Current thin-client remote desktop systems were designed for data-oriented applications over low-quality LAN links and they do not provide satisfactory end-user performance in enterprise environment for more and more popular graphical and multimedia applications. To improve perception of those applications in thin-client environment we propose architecture of a server-side Quality of Service (QoS) management component responsible for mapping application QoS requirements into network QoS. We analyze how service differentiation and traffic management techniques combined with user perception monitoring can be used in order to adjust network level resource allocation when performance of multimedia applications in remote desktop environment is not meeting user requirements. Our objective is to provide QoS-aware remote desktop systems which will be able to manage available resources in intelligent manner and meet end-user performance expectations. © 2005 IEEE

A demonstration of the FN packet marking probability

The effectiveness of queue management mechanisms relies on how good their control decisions will help in satisfying their goals regarding congestion avoidance and control.These decisions are implemented and compelled during the design of the packet mark probability and the mark activation functions. The design of Fast Congestion Notification (FN) drop/mark probability function enables the two control decisions, packet admissions and congestion control directing, to be made along with each other. This permits sending congestion avoidance notification as early as required even if the queue is almost empty, and preventing congestion notification even if the queue is almost full but the arrival rate is controllable. This leads to good buffer utilization and proper congestion detection. This paper demonstrates the drop/mark probability functions that the fast FN policy would exercise for different values of optimal queue size, and also for a specific optimal queue size value

A linear packet marking probability function for fast congestion notification (FN)

The efficiency of queue management mechanisms depends on how well their control decisions helps in satisfying their objectives regarding congestion avoidance and control. These decisions are implemented and compelled during the design of the packet mark probability and the mark activation functions. If a packet is dropped / marked rather than being allowed to the buffer, a congestion notification is delivered and the congestion avoidance and control carries on to be applied at the router. If the queue management mechanism realizes the need to apply more aggressive congestion control, the recently arrived packet should be dropped to provide early congestion notification. In this paper, we design a new packet drop probability function with a built-in drop activation function for Fast Congestion Notification (FN) mechanism. This design enables the two control decisions, packet admissions and congestion control directing, to be made along with each other. This permits sending congestion avoidance notification as early as required even if the queue is almost empty, and preventing congestion notification even if the queue is almost full but the arrival rate is controllable, thus the buffer is fully utilized and the congestion is detected properly

The FN quadratic marking/dropping probability function

The gateway queuing performance depends on the marking/dropping probability function chosen. This function plays an important role in managing the gateway buffer. It maps the current congestion level to marking/dropping probability that is applied to each arriving packet. Active queue management mechanisms drop arriving packets probabilistically before the gateway buffer gets full. Fast Congestion Notification (FN) mechanism is a proactive queue management mechanism that marks/drops packets before a buffer overflow happens to avoid congestion. FN avoids the queue overflows by controlling the instantaneous queue size below the optimal queue size, and control congestion by keeping the average arrival rate close to the outgoing link capacity.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 derivation of the FN quadratic marking/dropping probability function based on the assumption that the average packet arrival rate changes during the control time constant period with the constant acceleration

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

Network level performance of differentiated services (diffserv) networks

The Differentiated Services (DiffServ) architecture is a promising means of providing Quality of Service (QoS) in Internet. In DiffServ networks, three service classes, or Per-hop Behaviors (PHBs), have been defined: Expedited Forwarding (EF), Assured Forwarding (AF) and Best Effort (BE). In this dissertation, the performance of DiffServ networks at the network level, such as end-to-end QoS, network stability, and fairness of bandwidth allocation over the entire network have been extensively investigated. It has been shown in literature that the end-to-end delay of EF traffic can go to infinity even in an over-provisioned network. In this dissertation, a simple scalable aggregate scheduling scheme, called Youngest Serve First (YSF) algorithm is proposed. YSF is not only able to guarantee finite end-to-end delay, but also to keep a low scheduling complexity. With respect to the Best Effort traffic, Random Exponential Marking (REM), an existing AQM scheme is studied under a new continuous time model, and its local stable condition is presented. Next, a novel virtual queue and rate based AQM scheme (VQR) is proposed, and its local stability condition has been presented. Then, a new AQM framework, Edge-based AQM (EAQM) is proposed. EAQM is easier to implement, and it achieves similar or better performance than traditional AQM schemes. With respect to the Assured Forwarding, a network-assist packet marking (NPM) scheme has been proposed. It has been demonstrated that NPM can fairly distribute bandwidth among AF aggregates based on their Committed Information Rates (CIRs) in both single and multiple bottleneck link networks