Fuzzy Two Time-scale Congestion Control Algorithm

Improving performance of backpressured packet networks by integrating with an end-to-end congestion control algorithm

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.

Channel congestion is one of the most critical issues in IEEE 802.11p-based vehicular communications as it leads to the unreliability of safety applications. As a countermeasure, many Decentralized Congestion Control (DCC) algorithms have been proposed. One of the most prominent DCC algorithms is the message-rate based LIMERIC. Recently, algorithms have also been proposed to support higher vehicle density (better scalability). One of such algorithms is the combined message-rate and data-rate based congestion control algorithm (MD-DCC). MD-DCC can support around 2.7 times higher vehicular density than LIMERIC. However, if LIMERIC has been deployed, can MD-DCC be introduced and coexist well with LIMERIC. The objective of this paper is to investigate how MD-DCC coexists with LIMERIC. Given a scenario where vehicles may use either LIMERIC or MD-DCC, we study the impact of coexistence on channel load, fairness and reliability of vehicles at different densities. Simulation studies show that there is no significant degradation of reliability both for LIMERIC and MD-DCC at different densities. On the contrary, coexistence can improve the reliability of LIMERIC vehicles. Furthermore, MD-DCC can support vehicles at large densities even when it coexists with LIMERIC retaining its scalability. However, fair allocation of resources is not guaranteed when LIMERIC and MD-DCC coexist.

Chapter 5 - Congestion Control in High-Speed Networks

In recent years, hybrid congestion control (CC) algorithms that combine rule-based CC and learning-based CC have gained significant attention. They incorporate the fast adaption ability of learning-based CC and the stability of rule-based CC, tending to select the better-performing rate based on the network feedback. However, the practical implementation of such algorithms has revealed primary issues. Specifically, they require both CCs to run alternately, which results in a poorly performing CC continuing to run in the network. Moreover, hybrid CCs cannot converge to the optimal rate when both CCs perform poorly. This paper proposes Anole to address these issues. Anole has three main algorithmic contributions: 1) Anole always selects the better-performing CC, 2) Anole temporarily deprecates the consistently underperforming CC, 3) when both CCs pervform poorly, Anole infers the optimal sending rate based on the network feedback. We carry out comprehensive experiments in both emulated and real-world wired networks, as well as in real-world WiFi networks, to assess the performance of Anole. The experiment results demonstrate that Anole achieves approximately 6% higher throughput in real-world links and 34% lower delay in the 48Mbps link compared to the state-of-the-art CC. Anole also exhibits superior performance in adaptability and fair convergence.

In this paper, we study the performance of utility maximization congestion control over multihop CSMA-based networks. We consider decoupled vs. joint design of congestion control and medium access and consider unmodified MAC protocols such as IEEE 802.11. Networks employing such MAC protocols incur flow starvation both without congestion control and with existing TCP-based congestion control. We develop a framework to study key issues in such networks that are not incorporated by prior models, yet are critical to the performance of congestion control algorithms. We study the role of data transmission capacity that is location dependent and, even more, unknown. We show that for the case of consistent channel state, a single globally optimal data transmission capacity does not exist. Moreover, for the case of inconsistent channel state that arises due to the carrier sense mechanism itself, a data transmission capacity that provides convergence to perfectly fair rates does not exist, i.e., the congestion control algorithm converges to incorrect rates. We study the impact of inter-node collaboration within a contention region, and show that collaboration can alleviate these problems and ensure convergence to fair rates. Finally, we compare the performance of congestion control in a collaborative network with the performance of TCP, and show that TCP starves some flows, whereas congestion control with collaboration removes starvation, provides significantly better fairness, and achieves 17% higher aggregate throughput.

Congestion control (CC) is an indispensable component of transport protocols to prevent congestion collapse as it distributes the available bandwidth among all competing flows, ideally in a fair manner. It thus has a large impact on performance and there exists a constantly evolving set of CC algorithms, each addressing different performance needs. While the algorithms are commonly tested regarding the problems underlying their implementation, the interaction with existing algorithms is often not considered. Additionally considering the fact that content providers (CPs) such as content distribution networks (CDNs) are known to tune TCP stacks for performance gains, the large assortment of algorithms opens the door for custom parametrization and potentially unfair bandwidth sharing. In this paper, we thus empirically investigate if current Internet traffic generated by CPs still adheres to the conventional understanding of fairness. For this, we compare fairness properties of testbed hosts to actual traffic of six major CPs subject to different queue sizes and queueing disciplines in a home-user setting. Additionally, we investigate how mice and elephant flows from the different CPs interact. We find that some employed CC algorithms lead to significantly asymmetric bandwidth shares and very poor flow completion times for mice flows. Fortunately, AQMs such as FQ_CoDel are able to alleviate such unfairness.

In this chapter, layer-2 hop-by-hop congestion control mechanisms for wireless mesh networks are studied. First, background on development of congestion control as a research area is presented. Then, congestion is defined and the causes of congestion in a mesh network are identified. The steps and challenges for development of a congestion control protocol are explored by dividing congestion control mechanism into three main functions: congestion detection, signaling, and resolution. Stability and fairness in the context of rate control are studied, and global stability in the presence of delay is identified as the main challenge faced by hop-by-bop congestion control algorithms in multihop networks. The congestion control framework in the IEEE 802.11 draft standard on mesh networking is then presented. The chapter concludes with thoughts for practitioners and areas for future research in this field.

Congestion control enables network nodes to adopt certain approaches to avoid network congestion as much as possible, and respond when network congestion occurs. BBR is a transmission rate-based congestion control algorithm proposed by Google for Chromium QUIC and Linux kernel deployment. The new transmission protocol QUIC proposed by Google has a better congestion control mechanism than TCP. Based on the existing BBR congestion control algorithm, this paper proposes the IBCCA congestion control algorithm and evaluates the performance of the IBCCA, CUBIC, and BBR algorithms under the QUIC protocol in wireless LAN. When the network traffic burst flow is small or the burst duration is short, IBCCA achieves higher network goodput and lower transmission round-trip time. In the experiment of multi-stream transmission, the IBCCA algorithm achieves higher fairness while the good-put and RTT are at the same level. The BBR algorithm achieves a smaller RTT, and the goodput of the IBCCA algorithm is not much different from the CUBIC algorithm.

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.

In this paper we explore congestion control solutions in a network running the Named Data Networking (NDN) protocol. Since requested data can be retrieved from either original producers or in-network caches, the end-to-end connection oriented TCP congestion control solutions, such as BBR (Bottleneck Bandwidth and Round-trip propagation time) do not work well for NDN transport, especially in wireless networks. We propose a BBR-guided congestion control, BBR-CD, for bulk data fetching by a group of users. BBR-CD applies RTT filtering and interest scheduling to improve BBR's efficiency in NDN. Our evaluation shows that BBR-CD achieves much higher application goodput compared with ndncatchunks which implements the TCP AIMD and CUBIC congestion control algorithms. Moreover, compared with one-flow-per-file SIRC, an NDN congestion control algorithm that paces interests based on inter-data-gap, BBR-CD provides better fairness and bandwidth utilization. Finally, BBR-CD outperforms a direct adoption of the original BBR to NDN, suggesting that our changes to BBR are effective.

With the rapid development of information society, the number of information data transmitting in the Internet is growing quickly, so congestion control becomes very important and it is a hot research field on the Internet now. In this paper, the sliding window, reasons and TCP algorithms of congestion control such as slow start, congestion avoidance, fast retransmit and fast recovery are discussed. Different TCP versions about congestion control are studied and analyzed. As a result, improvements on the congestion control algorithm and the research is still an important topic in the study of Internet congestion control.

The main objective of congestion control is to best exploit the available network resources while preventing sustained overloads of network nodes and links. Appropriate congestion control mechanisms are essential to provide effcient operation of a network. Ensuring congestion control within vehicular ad hoc networks faces special challenges, due to the specificities of such environment (High mobility of nodes, high rate of topology changes, high variability in nodes density and neighborhood configuration, broadcast/geocast communication nature, etc.). In this context, we present in this paper a cooperative and fully distributed congestion control approach, based on dynamic scheduling and transmission of priority-based messages, to ensure reliable and safe communication architecture within VANET. Messages priorities are dynamically evaluated according to their types, the network context, and the neighboring nodes configuration. Considering the context of high reliability and real-time response required for intervehicular communications (including emergency breaking notification for example), we propose a complete validation method of our congestion control algorithms, taking into account reliability, temporal, and operational aspects.

In order to guarantee traffic flow medium in network, congestion control strategy is adopted in traffic flow medium. According to the delay sensitivity of flow medium data, this paper proposes a novel congestion control for traffic flow medium in network known as Adaptive Delay Congestion Control (ADCC). ADCC improves the QoS of multimedia stream in Network by detecting and discarding these packets that their accumulated delay exceeds multimedia stream's tolerance delay threshold, and maintain high bandwidth utilization. Another notable feature of the scheme is that ADCC implement congestion control by adaptive adjusting the switch device's queue length threshold according to propagation delay. Simulation results shows that the proposed scheme can effectively reduce the average delay than that of using traditional congestion control algorithm. Moreover, it is suitable to be used in the ever-changing network environment and can improve utilization of the network resources.