Simulation of Buffer Management Policies in Networks for Grids

International Journal of …, 2007

Computer Networks, 2001

The basic idea behind active queue management schemes such as random early detection (RED) is to detect incipient congestion early and to convey congestion noti®cation to the end-systems, allowing them to reduce their transmission rates before queues in the network over¯ow and packets are dropped. The basic RED scheme (and its newer variants) maintains an average of the queue length which it uses together with a number of queue thresholds to detect congestion. RED schemes drop incoming packets in a random probabilistic manner where the probability is a function of recent buer ®ll history. The objective is to provide a more equitable distribution of packet loss, avoid the synchronization of ows, and at the same time improve the utilization of the network. The setting of the queue thresholds in RED schemes is problematic because the required buer size for good sharing among TCP connections is dependent on the number of TCP connections using the buer. This paper describes a technique for enhancing the eectiveness of RED schemes by dynamically changing the threshold settings as the number of connections (and system load) changes. Using this technique, routers and switches can eectively control packet losses and TCP timeouts while maintaining high link utilization.

Computer Communications, 2004

With the advent of computational grids, networking performance over the wide-area network (WAN) has become a critical component in the grid infrastructure. Unfortunately, many high-performance grid applications only use a small fraction of their available bandwidth because operating systems and their associated protocol stacks are still tuned for yesterday's network speeds. As a result, network gurus undertake the tedious process of manually tuning system buffers to allow TCP flow control to scale to today's WAN environments. And although recent research has shown how to set the size of these system buffers automatically at connection setup , the buffer sizes are only appropriate at the beginning of the connection's lifetime. To address these problems, we describe an automated and lightweight technique called Dynamic Right-Sizing that can improve throughput by as much as an order of magnitude while still abiding by TCP semantics. We show the performance of two user-space implementations of DRS: drsFTP and DRS-enabled GridFTP.

IEEE Access

Traffic classification networks have various applications for data transmissions to ensure quality of service (QoS) for various classes of traffic at the routers. Multi-level random early detection (MRED) scheduling algorithm is used to manage resources at the routers guaranteeing QoS. However, the MRED queue mechanism is insensitive to traffic and difficult to set parameters, for the average queue is sensitive to high congestion level of multi-flow which is a major issue affecting the performance of the queue in the networks. This paper propose a new scheduling algorithm that manages congestion level by increasing the stability of parameters, using dynamic weighted traffic with redefining probability drop traffic in the MRED algorithm. The results present the performance algorithm while utilizing the reference algorithms, improving the bandwidth fairness and average throughput and reduce the average delay and packet drop. Quality of service, scheduling algorithm, marker algorithm, classes of traffic, active queue management. Weighted Fair Queuing (WFQ), and Weighted Random Early Detection (WRED) [5]-[7]. This paper presents the efficient control of MRED scheduling algorithm by a modified weighted buffer, which is redefined to determine probability drop traffic. This kind of algorithm is suitable for the TCP/UDP protocol to provide an efficient solution to manage drop traffic and reduce average delay at core routers. We also investigate the proposed improvements to bandwidth fairness along with efficient optimization to alleviate the problem at the edge router. The paper is organized as follows. Section II outlines the related works and discusses this work in relation to previous scientific studies. Section III provides the proposed technique that calculates the average queue length to correct loss traffic in the MRED algorithm. Section IV presents the simulation parameters and performance metrics. Section V discusses the obtained results and its analysis. Section VI provides the conclusions. This section provides a brief overview of active queue management algorithms, including RED, ARED, and WRED, as well as the traffic marker OtswTCM.

2003

With the advent of computational grids, networking performance over the wide-area network (WAN) has become a critical component in the grid infrastructure. Unfortunately, many high-performance grid applications only use a small fraction of their available bandwidth because operating systems and their associated protocol stacks are still tuned for yesterday's WAN speeds. As a result, network gurus undertake the tedious process of manually tuning system buffers to allow TCP flow control to scale to today's WAN grid environments. And although recent research has shown how to set the size of these system buffers automatically at connection setup , the buffer sizes are only appropriate at the beginning of the connection's lifetime. To address these problems, we describe an automated and lightweight technique called Dynamic Right-Sizing that can improve throughput by as much as an order of magnitude while still abiding by TCP semantics.

IEEE/ACM Transactions on Networking, 2002

In order to stem the increasing packet loss rates caused by an exponential increase in network traffic, the IETF has been considering the deployment of active queue management techniques such as RED [14]. While active queue management can potentially reduce packet loss rates in the Internet, we show that current techniques are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they use queue lengths as the indicator of the severity of congestion. In light of this observation, a fundamentally different active queue management algorithm, called BLUE, is proposed, implemented and evaluated. BLUE uses packet loss and link idle events to manage congestion. Using both simulation and controlled experiments, BLUE is shown to perform significantly better than RED both in terms of packet loss rates and buffer size requirements in the network. As an extension to BLUE, a novel technique based on Bloom filters [2] is described for enforcing fairness among a large number of flows. In particular, we propose and evaluate Stochastic Fair BLUE (SFB), a queue management algorithm which can identify and rate-limit non-responsive flows using a very small amount of state information.

Proc. of the Intl. Journal …, 2004

International Journal of Distributed and Parallel systems

In IP networks, AQM attempts to provide high network utilization with low loss and low delay by regulating queues at bottleneck links. Many AQM algorithms have been proposed, most suffer from instability of queue, bursty packet drop, require careful configuration of control parameters, or slow response to dynamic traffic changes and unfairness. The deployment of active queue management techniques such as RED based is used that results in increased bursty packet loss and unfairness caused by an exponential increase in network traffic. The inherent problem with these queue management algorithms is that they all use queue lengths as the indicator of the severity of congestion. In order to solve this problem, a new active queue management algorithm called FAVQCHOKe is proposed. In this paper, arrival rate at the network link is maintained as a principal measure of congestion to improve the transient performances of the system and ensures the entire utilization of link capacity. In addition this proposed algorithm uses queue length and flow information that enhances fairness. This characteristic is particularly beneficial to real-time multimedia applications. Further, FAVQCHOKe achieves the above while maintaining high link utilization and low packet loss. This paper discusses about the inherent weaknesses of current techniques and how the proposed algorithm overcomes the weaknesses and ensures high degree of effectiveness in the performance of the system.

1999

In order to stem the increasing packet loss rates caused by an exponential increase in network traffic, the IETF is considering the deployment of active queue management techniques such as RED . While active queue management can potentially reduce packet loss rates in the Internet, this paper shows that current techniques are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they all use queue lengths as the indicator of the severity of congestion. In light of this observation, a fundamentally different active queue management algorithm called BLUE is proposed. BLUE uses packet loss and link idle events to manage congestion. Using simulation and controlled experiments, BLUE is shown to perform significantly better than RED both in terms of packet loss rates and buffer size requirements in the network. As an extension to BLUE, a novel technique for enforcing fairness among a large number of flows is described. In particular, this paper proposes and evaluates Stochastic Fair BLUE (SFB), a queue management algorithm which can identify and rate-limit non-responsive flows using a very small amount of state information.

Active queue management (AQM) schemes have motivated many researchers to investigate more effective methods to control network congestion. Most AQM schemes are evaluated by their designers on the basis of router-centric metrics, such as queuing delay, link utilization and packet drop ratio. These metrics are important to network operators but they may not reflect the quality of service delivered to end-users. In this paper we propose a method aimed to provide users with better services in terms of end-to-end delay and packet loss ratio. The method captures a significant traffic increase at an early stage and signals TCP sources to slow down. In this way, TCP can quickly adjust the transmission rate, and thereby prevent overloading the network. In addition to RED, another two prominent AQM schemes, namely, random early marking (REM) and adaptive RED (ARED), are compared with the proposed method. Simulation results show that under various network loads and a range of network propagati...