Analysis of Reverse Traffic in Delay-Based Congestion Control

Problem statement: Transmission Control Protocol is the Internet’s most widely used transport control protocol. TCP’s strength lies in the adaptive nature of its congestion avoidance and control algorithm and its retransmission mechanism. In TCP Vegas rerouting (a path), which change the propagation delay of the connection and this may be able to result in a substantial decrease in through put. An enhanced algorithm for TCP in wireless Ad Hoc networks is needed to obtain a fairer share of the available bandwidth, tackle re-routing problems and solve the problems associated with older TCP Vegas flows. Approach: TCP-Vegas uses an Estimation of the propagation delay, base RTT, to adjust its window size and it is very important for a TCP Vegas connection to be able to have an accurate estimation. Results: One of the issues is rerouting (a path), which change the propagation delay of the connection and this may be able to result in a substantial decrease in through put. The issue identified with TCP Vegas was reinvestigated and to address them, a modification to TCP Vegas’s congestion avoidance algorithm is proposed. Conclusion: This modified TCP enhancement algorithams is shown to obtain a fairer share of the available bandwidth, tackle re-routing problems and solve the problems associated with older TCP Vegas flows.

While it has been shown that TCP Vegas provides better performance compared to TCP Reno, studies have identified various issues associated with the protocol in mobile ad hoc networks. We propose modifications to the congestion avoidance mechanism of the TCP Vegas to overcome these limitations. Our solution, named TCP Vegas_M, is dependent on FEDM fuzzy logic theory to distinguish network congestion states and wireless channel states, and based on ad hoc networks states (congestion, uncertain, and bit error), TCP sender adopt different congestion avoidance algorithms to control congestion window size, aims is to optimize ad hoc network throughput and achieve better performance. Simulation experiments show that TCP Vegas-M is able to overcome several of the identified problems-it can obtain more throughput than TCP Reno and TCP Vegas, and avoid oscillation of TCP sender congestion window. Keywords: mobile ad hoc network, TCP Vegas, fuzzy logic theory, round trip time

The congestion control and avoidance algorithms can be divided into source and link algorithms. The source algorithms are based on ’pipe’ model; which includes TCP Tahoe, TCP Reno, TCP NewReno, SACK and TCP Vegas. In this paper, we present a novel congestion control source algorithm-FAV(Forecast And Verify), which measures packets delay to forecast whether there will be congestion in network, and uses ECN to verify whether the forecast is precise or not. Experiments are performed by ns2 to compare FAV with TCP Reno and TCP Vegas, and the results imply that FAV algorithm can decrease loss rate and link delay efficiently, and keep link utilization high. We think FAV can control the congestion better than other source algorithms.

Previous analytic models of TCP Vegas throughput have been developed for loss-free (all-Vegas) networks. This work develops a simple and accurate analytic model for the throughput of a TCP Vegas bulk transfer in the presence of packet loss, as a function of average round trip time, minimum round trip time, and loss rate for the transfer. Similar models have previously been developed for TCP Reno. However, several aspects of TCP Vegas need to be treated differently than their counterparts in Reno. The proposed model captures the key innovative mechanisms that Vegas employs during slow start, congestion avoidance, and congestion recovery. The results include (1) a simple, validated model of TCP Vegas throughput that can be used for equation-based rate control of other flows such as UDP streams, (2) a simple formula to determine, from the measured packet loss rate, whether the network buffers are overcommitted and thus the TCP Vegas flow cannot reach the specified target lower threshold on throughput, (3) new insights into the design and performance of TCP Vegas, and (4) comparisons between TCP Vegas and TCP Reno including new insights regarding incremental deployment of TCP Vegas.

Previous analytic models of TCP Vegas throughput have been developed for loss-free (all-Vegas) networks. This work develops a simple and accurate analytic model for the throughput of a TCP Vegas bulk transfer in the presence of packet loss, as a function of average round trip time, minimum round trip time, and loss rate for the transfer. Similar models have previously been developed for TCP Reno. However, several aspects of TCP Vegas need to be treated differently than their counterparts in Reno. The proposed model captures the key innovative mechanisms that Vegas employs during slow start, congestion avoidance, and congestion recovery. The results include (1) a simple, validated model of TCP Vegas throughput that can be used for equation-based rate control of other flows such as UDP streams, (2) a simple formula to determine, from the measured packet loss rate, whether the network buffers are overcommitted and thus the TCP Vegas flow cannot reach the specified target lower threshold on throughput, (3) new insights into the design and performance of TCP Vegas, and (4) comparisons between TCP Vegas and TCP Reno including new insights regarding incremental deployment of TCP Vegas.

To alleviate the lower performance of Transmission Control Protocol (TCP) congestion control over complex network, especially the high latency and packet loss scenario, Google proposed the Bottleneck Bandwidth and Round-trip propagation time (BBR) congestion control algorithm. In contrast with other TCP congestion control algorithms, BBR adjusted transfer data by maximizing delivery rate and minimizing delay. However, some evaluation experiments have shown that the persistent queues formation and retransmissions in the bottleneck can lead to serious fairness issues between BBR flows with different round-trip times (RTTs). They pointed out that small RTT differences cause unfairness in the throughput of BBR flows and flows with longer RTT can obtain higher bandwidth when competing with the shorter RTT flows. In order to solve this fairness problem, an adaptive congestion window of BBR is proposed, which adjusts the congestion window gain of each BBR flow in network load. The proposed algorithms alleviate the RTT fairness issue by controlling the upper limit of congestion window according to the delivery rate and queue status. In the Network Simulator 3 (NS3) simulation experiment, it shows that the adaptive congestion window of BBR (BBR-ACW) congestion control algorithm improves the fairness by more than 50% and reduces the queuing delay by 54%, compared with that of the original BBR in different buffer sizes.

ABSTRACTAlthough delay‐based congestion control protocols such as FAST Transmission Control Protocol (TCP) promise to deliver better performance than traditional TCP Reno, they have not yet been widely incorporated to the Internet. Several factors have contributed to their lack of deployment. Probably, the main contributing factor is that they are not able to compete fairly against loss‐based congestion control protocols. In fact, the transmission rate in equilibrium of delay‐based approaches is always less than their fair share when they share the network with traditional TCP Reno derivatives that employ packet losses as their congestion signal. There are also other performance impairments caused by the sensitivity to errors in the measurement of the congestion signal (queuing delay) that reduce the efficiency and the intra‐protocol fairness of the algorithms. In this paper, we report, analyse and discuss some recent proposals in the literature to improve the dynamic behaviour of delay‐based congestion control algorithms, FAST in particular. The coexistence of sources reacting differently to congestion, the identification of congestion appearance in the reverse path and thepersistent congestionproblem are the issues specifically addressed. Copyright © 2011 John Wiley & Sons, Ltd.

A single flow stream could be divided into several sub-flows to be sent across multiple paths. This method obtains obvious advantages against traditional TCP as it maintains higher reliability and makes bettaer use of the network resources. Congestion control algorithm is an essential part to be considered. This paper first reviews the existing multipath TCP congestion control algorithms and then analyzes and formulates the goals and problems need to be achieved and solved. A delay-based congestion control algorithm named Weighted Vegas (wVegas) is provided. Finally, two possible modifications are demonstrated including adjusting the congestion control window according to how far the path is from congestion and redefining the behavior when loss occurs.

TCP congestion control has been designed to ensure Internet stability along with fair and efficient allocation of the network bandwidth. During the last decade, many congestion control algorithms have been proposed to improve the classic Tahoe/Reno TCP Congestion control. This paper aims at evaluating and comparing three control algorithms, which are Westwood+, New Reno and Vegas TCP. Simulation scenarios are carefully designed in order to investigate goodput, fairness and friendliness provided by each of the algorithms. results show that Westwood+ TCP is friendly towards New Reno TCP and improves fairness in bandwidth allocation whereas Vegas TCP is fair but is not able to grab its bandwidth share when coexisting with Reno or in the presence of reverse traffic because of its RTT-based congestion detection mechanism. Finally results show that Westwood* remarkably improves utilization of wireless links that are affected by losses not due to congestion.

Google proposed a new congestion control algorithm (CCA) based on bottleneck bandwidth and round-trip propagation time (BBR), which is considered to open a new era of congestion control. BBR creates a network path model by measuring the available bottleneck bandwidth and the minimum round-trip time (RTT) to maximize delivery rate and minimize latency. The BBR v2 algorithm is a recently updated version by Google, which aims to improve some of the problems in the original BBR (BBRv1) algorithm, such as interprotocol fairness issues, RTT fairness issues, and excessive retransmissions. The BBRv2 evaluation results show that it can improve the coexistence with the loss_based algorithm and alleviate some of the shortcomings in BBRv1. However, when multiple BBRv2 flows enter the same link at different times, fair convergence cannot be achieved, and RTT fairness still exists. Based on these problems, we analyze the root cause and proposed an improved algorithm BBRv2+, which uses flow-aware explicit congestion notification (ECN) to quantify queue information and feedback on the accurate congestion degree. BBRv2+ algorithm can avoid blind window constraints and selectively mark packets so that different flows can converge to fairness. In the simulation experiment of Network Simulator 3 (NS3), the results show that the BBRv2+ algorithm can improve intraprotocol fairness and RTT fairness and ensure bandwidth utilization and interprotocol fairness.

Google proposed a new TCP congestion control algorithm (CCA), Bottleneck Bandwidth and Round-trip propagation time (BBR) which has opened up new dimensions in congestion control. BBR tries to operate near Kleinrock's operating point to avoid excessive queue formation at the bottleneck and to use the link bandwidth optimally. BBR creates a model of the network path by measuring the bottleneck bandwidth and minimum round-trip time (RTT) to maximize the delivery rate and minimize latency. BBR v2 is an updated version of BBR which addresses many shortcomings of the original BBR (BBR v1) such as interprotocol fairness, RTT fairness, and excessive retransmissions. However, BBR v2 has certain limitations in its operation in IEEE 802.11ac (Wi-Fi 5) networks. The default BBR v2 limits the throughput of Wi-Fi 5 and an increased latency has been observed. This is because the Wi-Fi 5 frame aggregation logic is underutilized and fewer frames are being sent to the Wi-Fi 5 interface. In this paper, we have proposed BBR-n (BBR new) which provides better throughput than the generic BBR v2 in the Wi-Fi 5 networks. Real-time experiments were performed over a physical testbed using Flent to confirm that BBR-n achieves over double throughput as compared to generic BBR v2 and reduced latency in networks as compared to pure loss-based variants such as Cubic and Reno.

In this paper, we describe the synthesis of robust and non-fragile H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">infin</sub> state feedback rate-based congestion controllers for the ATM network system with affine parameter uncertainties and round trip delay, as well as static state feedback congestion controller with polytopic uncertainty. For practical congestion control design, the round trip delay commonly appears on transmission line and it is important factor of congestion control in ABR services. Various congestion control algorithm has been researched already, but we approach the problem with other method - Parameterized Linear Matrix Inequalities (PLMIs), that is, LMIs whose coefficients are functions of a parameter confined to a compact set. And we show that the resulting controller guarantees the asymptotic stability and disturbance attenuation of the closed loop system.

In 2016, Google proposed the bottleneck bandwidth round-trip propagation time (BBR) as a new congestion control algorithm for improving network speed. As BBR has different behavioral characteristics from loss-based congestion control, it must ensure the coexistence between congestion control algorithms. However, throughput imbalance has been reported in a competition between BBR and loss-based congestion control. In this paper, we propose an opponent congestion control identification model of BBR (OI-BBR) with machine learning to improving inter-protocol fairness. In the emulation experiments, we confirmed that OI-BBR based on the proposed model improved the inter-protocol fairness by operating differently according to the opponent congestion control algorithms.

The last three decades have seen much evolution in web and network protocols: amongst them, a transition from HTTP/1.1 to HTTP/2 and a shift from loss-based to delay-based TCP congestion control algorithms. This paper argues that these two trends come at odds with one another, ultimately hurting web performance. Using a controlled synthetic study, we show how delay-based congestion control protocols (e.g., BBR and CUBIC + Hybrid Slow Start) result in the underestimation of the available congestion window in mobile networks, and how that dramatically hampers the effectiveness of HTTP/2. To quantify the impact of such finding in the current web, we evolve the web performance toolbox in two ways. First, we develop Igor, a client-side TCP congestion control detection tool that can differentiate between loss-based and delay-based algorithms by focusing on their behavior during slow start. Second, we develop a Chromium patch which allows fine-grained control on the HTTP version to be used per domain. Using these new web performance tools, we analyze over 300 real websites and find that 67% of sites relying solely on delay-based congestion control algorithms have better performance with HTTP/1.1.

A network is very important for fast communication in real life but it is suffered from many problems and one of them is packets loss due to congestion. Congestion Control helps to prevent internet from gridlock state. When a packets switch becomes congested, its buffer can overflow and packets loss can occur. The internet avoids this problem by forcing end system to decrease the rate of sending packets into the network during congestion period. The end system uses algorithm to control the congestion is called Congestion Control (CC) algorithm. The CC algorithm has three major components additive-increase, multiplicative-decrease and slow-start. Accumulation-based congestion control (ACC) has two mechanism, first is TCP Vegas which is used to control the congestion by estimating the accumulation at sender end. Another is, Monaco scheme that solve problems of TCP Vegas by employing an out-of-band, receiver-based accumulation estimator, with the support of two FIFO priority queues. These schemes suffer from router buffer scalability problem which is solved by the use of Active Queue Management (AQM) .This paper illustrates the AQM scheme on the basis of throughput, fairness, and scalability and these parameters are analyzed by Network Simulator (NS-2) using dumb-bell topology, single bottleneck.