Active Queue Management via Event-Driven Feedback Control

Active queue management (AQM) is investigated to avoid incipient congestion in gateways to complement congestion control run by the transport layer protocol such as the TCP. Most existing work on AQM can be categorized as (1) ad-hoc event-driven control and (2) time-driven feedback control approaches based on control theory. Ad hoc event-driven approaches for congestion control, such as RED (random early detection), lack a mathematical model. Thus, it is hard to analyze their dynamics and tune the parameters. Time-driven control theoretic approaches based on solid mathematical models have drawbacks too. As they sample the queue length and run AQM algorithm at every fixed time interval, they may not be adaptive enough to an abrupt load surge. Further, they can be executed unnecessarily often under light loads due to the time-driven nature. To seamlessly integrate the advantages of both event-driven and control-theoretic time-driven approaches, we present an event-driven feedback control approach based on formal control theory. As our approach is based on a mathematical model, its performance is more analyzable and predictable than ad hoc event-driven approaches are. Also, it is more reactive to dynamic load changes due to its event-driven nature. Our simulation results show that our event-driven controller effectively maintains the queue length around the specified set-point. It achieves shorter E2E (end-to-end) delays and smaller E2E delay fluctuations than several existing AQM approaches, which are ad hoc event-driven and based on time-driven control theory, while achieving almost the same E2E delays and E2E delay fluctuations as the two other advanced control theoretic AQM approaches. Further, our AQM algorithm is invoked much less frequently than the tested baseline

Congestion Control for Streaming Media

The Internet has assumed the role of the underlying communication network for applications such as file transfer, electronic mail, Web browsing and multimedia streaming. Multimedia streaming, in particular, is growing with the growth in power and connectivity of today\u27s computers. These Internet applications have a variety of network service requirements and traffic characteristics, which presents new challenges to the single best-effort service of today\u27s Internet. TCP, the de facto Internet transport protocol, has been successful in satisfying the needs of traditional Internet applications, but fails to satisfy the increasingly popular delay sensitive multimedia applications. Streaming applications often use UDP without a proper congestion avoidance mechanisms, threatening the well-being of the Internet. This dissertation presents an IP router traffic management mechanism, referred to as Crimson, that can be seamlessly deployed in the current Internet to protect well-behaving traffic from misbehaving traffic and support Quality of Service (QoS) requirements of delay sensitive multimedia applications as well as traditional Internet applications. In addition, as a means to enhance Internet support for multimedia streaming, this dissertation report presents design and evaluation of a TCP-Friendly and streaming-friendly transport protocol called the Multimedia Transport Protocol (MTP). Through a simulation study this report shows the Crimson network efficiently handles network congestion and minimizes queuing delay while providing affordable fairness protection from misbehaving flows over a wide range of traffic conditions. In addition, our results show that MTP offers streaming performance comparable to that provided by UDP, while doing so under a TCP-Friendly rate

congestion control of data network by using anti-windup approach

Producción CientíficaAn Active Queue Management (AQM) scheme is design to control congestion in data networks, which includes anti-windup to deal with control signal saturation. More precisely, a methodology is proposed to design advanced AQM systems capable of regulating queue size even in the presence of significant disturbances. Hence, we first provide sufficient conditions for stabilization for the equivalent class of systems, which are derived in terms of LMI: this makes possible to derive optimization solutions that ensure performance and stability for a large domain of initial conditions. This approach is validated with a numerical example that illustrates the methodology, and the improvements with respect to previous congestion control solutions

Active queue management with discrete sliding modes in TCP networks

In this paper, a new active queue management (AQM) algorithm for data traffic control in TCP/IP networks is developed. The algorithm design is based on the principles of discrete sliding-mode control. Unlike majority of earlier studies, the design procedure considers the effects of both non-negligible delay in transferring data and feedback information and unpredictable capacity variations. The switching function is selected to incorporate a delay compensation mechanism, which ensures efficient network operation even for large bandwidthdelay product connections. The proposed algorithm, implemented as a packet marking scheme, is tested in discrete event ns-2 simulator. The results show that the algorithm provides fast convergence to steady state after sudden, unanticipated capacity changes. By generating smaller overshoots, the proposed algorithm also allows for reducing buffer space requirements to avoid packet loss as compared to the benchmark AQM solutions

On Designing Lyapunov-Krasovskii Based AQM for Routers Supporting TCP Flows

For the last few years, we assist to a growing interest of designing AQM (Active Queue Management) using control theory. In this paper, we focus on the synthesis of an AQM based on the Lyapunov theory for time delay systems. With the help of a recently developed Lyapunov-Krasovskii functional and using a state space representation of a linearized fluid model of TCP, two robust AQMs stabilizing the TCP model are constructed. Notice that our results are constructive and the synthesis problem is reduced to a convex optimization scheme expressed in terms of linear matrix inequalities (LMIs). Finally, an example extracted from the literature and simulations via {\it NS simulator} support our study

Congestion mitigation in LTE base stations using radio resource allocation techniques with TCP end to end transport

As of 2019, Long Term Evolution (LTE) is the chosen standard for most mobile and fixed wireless data communication. The next generation of standards known as 5G will encompass the Internet of Things (IoT) which will add more wireless devices to the network. Due to an exponential increase in the number of wireless subscriptions, in the next few years there is also an expected exponential increase in data traffic. Most of these devices will use Transmission Control Protocol (TCP) which is a type of network protocol for delivering internet data to users. Due to its reliability in delivering data payload to users and congestion management, TCP is the most common type of network protocol used. However, the ability for TCP to combat network congestion has certain limitations especially in a wireless network. This is due to wireless networks not being as reliable as fixed line networks for data delivery because of the use of last mile radio interface. LTE uses various error correction techniques for reliable data delivery over the air-interface. These cause other issues such as excessive latency and queuing in the base station leading to degradation in throughput for users and congestion in the network. Traditional methods of dealing with congestion such as tail-drop can be inefficient and cumbersome. Therefore, adequate congestion mitigation mechanisms are required. The LTE standard uses a technique to pre-empt network congestion by a mechanism known as Discard Timer. Additionally, there are other algorithms such as Random Early Detection (RED) that also are used for network congestion mitigation. However, these mechanisms rely on configured parameters and only work well within certain regions of operation. If the parameters are not set correctly then the TCP links can experience congestion collapse. In this thesis, the limitations of using existing LTE congestion mitigation mechanisms such as Discard Timer and RED have been explored. A different mechanism to analyse the effects of using control theory for congestion mitigation has been developed. Finally, congestion mitigation in LTE networks has been addresses using radio resource allocation techniques with non-cooperative game theory being an underlying mathematical framework. In doing so, two key end-to-end performance measurements considered for measuring congestion for the game theoretic models were identified which were the total end-to-end delay and the overall throughput of each individual TCP link. An end to end wireless simulator model with the radio access network using LTE and a TCP based backbone to the end server was developed using MATLAB. This simulator was used as a baseline for testing each of the congestion mitigation mechanisms. This thesis also provides a comparison and performance evaluation between the congestion mitigation models developed using existing techniques (such as Discard Timer and RED), control theory and game theory. As of 2019, Long Term Evolution (LTE) is the chosen standard for most mobile and fixed wireless data communication. The next generation of standards known as 5G will encompass the Internet of Things (IoT) which will add more wireless devices to the network. Due to an exponential increase in the number of wireless subscriptions, in the next few years there is also an expected exponential increase in data traffic. Most of these devices will use Transmission Control Protocol (TCP) which is a type of network protocol for delivering internet data to users. Due to its reliability in delivering data payload to users and congestion management, TCP is the most common type of network protocol used. However, the ability for TCP to combat network congestion has certain limitations especially in a wireless network. This is due to wireless networks not being as reliable as fixed line networks for data delivery because of the use of last mile radio interface. LTE uses various error correction techniques for reliable data delivery over the air-interface. These cause other issues such as excessive latency and queuing in the base station leading to degradation in throughput for users and congestion in the network. Traditional methods of dealing with congestion such as tail-drop can be inefficient and cumbersome. Therefore, adequate congestion mitigation mechanisms are required. The LTE standard uses a technique to pre-empt network congestion by a mechanism known as Discard Timer. Additionally, there are other algorithms such as Random Early Detection (RED) that also are used for network congestion mitigation. However, these mechanisms rely on configured parameters and only work well within certain regions of operation. If the parameters are not set correctly then the TCP links can experience congestion collapse. In this thesis, the limitations of using existing LTE congestion mitigation mechanisms such as Discard Timer and RED have been explored. A different mechanism to analyse the effects of using control theory for congestion mitigation has been developed. Finally, congestion mitigation in LTE networks has been addresses using radio resource allocation techniques with non-cooperative game theory being an underlying mathematical framework. In doing so, two key end-to-end performance measurements considered for measuring congestion for the game theoretic models were identified which were the total end-to-end delay and the overall throughput of each individual TCP link. An end to end wireless simulator model with the radio access network using LTE and a TCP based backbone to the end server was developed using MATLAB. This simulator was used as a baseline for testing each of the congestion mitigation mechanisms. This thesis also provides a comparison and performance evaluation between the congestion mitigation models developed using existing techniques (such as Discard Timer and RED), control theory and game theory

iRED: A disaggregated P4-AQM fully implemented in programmable data plane hardware

Routers employ queues to temporarily hold packets when the scheduler cannot immediately process them. Congestion occurs when the arrival rate of packets exceeds the processing capacity, leading to increased queueing delay. Over time, Active Queue Management (AQM) strategies have focused on directly draining packets from queues to alleviate congestion and reduce queuing delay. On Programmable Data Plane (PDP) hardware, AQMs traditionally reside in the Egress pipeline due to the availability of queue delay information there. We argue that this approach wastes the router's resources because the dropped packet has already consumed the entire pipeline of the device. In this work, we propose ingress Random Early Detection (iRED), a more efficient approach that addresses the Egress drop problem. iRED is a disaggregated P4-AQM fully implemented in programmable data plane hardware and also supports Low Latency, Low Loss, and Scalable Throughput (L4S) framework, saving device pipeline resources by dropping packets in the Ingress block. To evaluate iRED, we conducted three experiments using a Tofino2 programmable switch: i) An in-depth analysis of state-of-the-art AQMs on PDP hardware, using 12 different network configurations varying in bandwidth, Round-Trip Time (RTT), and Maximum Transmission Unit (MTU). The results demonstrate that iRED can significantly reduce router resource consumption, with up to a 10x reduction in memory usage, 12x fewer processing cycles, and 8x less power consumption for the same traffic load; ii) A performance evaluation regarding the L4S framework. The results prove that iRED achieves fairness in bandwidth usage for different types of traffic (classic and scalable); iii) A comprehensive analysis of the QoS in a real setup of a DASH) technology. iRED demonstrated up to a 2.34x improvement in FPS and a 4.77x increase in the video player buffer fill.Comment: Preprint (TNSM under review