GA-PSO-Optimized Neural-Based Control Scheme for Adaptive Congestion Control to Improve Performance in Multimedia Applications

Active queue control aims to improve the overall communication network throughput while providing lower delay and small packet loss rate. The basic idea is to actively trigger packet dropping (or marking provided by explicit congestion notification (ECN)) before buffer overflow. In this paper, two artificial neural networks (ANN)-based control schemes are proposed for adaptive queue control in TCP communication networks. The structure of these controllers is optimized using genetic algorithm (GA) and the output weights of ANNs are optimized using particle swarm optimization (PSO) algorithm. The controllers are radial bias function (RBF)-based, but to improve the robustness of RBF controller, an error-integral term is added to RBF equation in the second scheme. Experimental results show that GA- PSO-optimized improved RBF (I-RBF) model controls network congestion effectively in terms of link utilization with a low packet loss rate and outperform Drop Tail, proportional-integral (PI), random exponential marking (REM), and adaptive random early detection (ARED) controllers.Comment: arXiv admin note: text overlap with arXiv:1711.0635

Functional Optimization Models for Active Queue Management

Active Queue Management (AQM) is an important problem in networking. In this paper, we propose a general functional optimiza-tion model for designing AQM schemes. Unlike the previous static func-tion optimization models based on the artificial notion of utility function, the proposed dynamic functional optimization formulation allows us to directly characterize the desirable system behavior of AQM and design AQM schemes to optimally control the dynamic behavior of the system. Such a formulation also allows adaptive control which enables the AQM scheme to continuously adapt to dynamic changes of networking con-ditions. In this paper, we present the Pontryagin minimum principle, a necessary condition, for the functional optimization model of AQM with TCP AIMD congestion control. As an example, we investigate a queu-ing stability criteria and apply the necessary conditions to optimize the functional model

Flower Pollination Algorithm to Tune PID Controller of TCP/AQM Wireless Networks

The current study aims to conduct a simulation that is useful in developing an appropriate design that addresses the problem of congestion in the Internet network through controlling the queue of the router. The simulation is conducted through the proposed model for simulation with different control systems that help in raising the quality of performance such as traditional Proportional Integral Derivative (PID) and advanced optimal by Flower Pollination Algorithm  (FPA). It depends for Transmission Control Protocol/ Active Queue Management( TCP/AQM )simulation model for a linear system and another non-linear system. To adjust the network work and raise the level of performance, different control systems were chosen, taking into account all the things that appear through conducting experiments and for different purposes. One of the most important things that must be taken into consideration is the system disturbances as a result of the volume and values of the data, causing congestion . It was shown through the results of the experiments that were conducted considering the cases of the linear and nonlinear system to pass data traffic in the network and by adopting the different techniques of the control units, the preference of optimizasion systems over the traditional ones, as well as the preference of the traditional over  without control in close loop, is the improvement of the performance of linear systems compared to the open and closed system without control. The simulation results showed that very clear the superiority of the optimization by FPA-PID controller over the conventional system (PID)  , as well as very clear the superiority of  the traditional system (PID)over closed system without control and open loop system

Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab

Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques

Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab

Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques

Control de Congestión TCP y mecanismos AQM

En los últimos años se ha ido poniendo énfasis particularmente en la importancia del retraso sobre la capacidad. Hoy en día, nuestras redes se están volviendo más y más sensibles a la latencia debido a la proliferación de aplicaciones y servicios como el VoIP, la IPTV o el juego online donde un retardo bajo es esencial para un desempeño adecuado y una buena experiencia de usuario. La mayor parte de este retraso innecesario se debe al mal funcionamiento de algunos búferes que pueblan internet. En vez de desempeñar la tarea para la que fueron creados, absorber eventuales ráfagas de paquetes con el fin de prevenir su pérdida, hacen creer al mecanismo de control de congestión que la ruta hacia el destino actual tiene más ancho de banda que el que posee realmente. Cuando la pérdida de paquetes ocurre, si es que lo hace, es demasiado tarde y el daño en el enlace, en forma de tiempo de transmisión adicional, ya se ha producido. En este trabajo de fín de grado intentaremos arrojar luz sobre una solución específica cuyo objetivo es el de reducir el retardo extra producido por esos hinchados búferes, la Gestión Avanzada de Colas o Active Queue Management (AQM). Hemos testeado un grupo de estos algoritmos AQM junto con diferentes modificaciones del control de congestión de TCP con el fín de entender las interacciones generadas entre esos dos mecanismos, realizando simulaciones en varios escenarios caracterísiticos tales como enlaces transoceánicos o enlaces de acceso a red, entre otros.In recent years, the relevance of delay over throughput has been particularly emphasized. Nowadays our networks are getting more and more sensible to latency due to the proliferation of applications and services like VoIP, IPTV or online gaming where a low delay is essential for a proper performance and a good user experience. Most of this unnecessary delay is created by the misbehaviour of many bu ers that populate Internet. Instead of performing the task for what they were created for, absorbing eventual packet bursts to prevent loss, they deceive the sender's congestion control mechanisms into believing that the current path to the destination has more bandwidth than it really has. When the loss event occurs, if it does, it's too late and the damage on the path, in terms of additional transmission time, has been done. On this bachelor thesis we will try to throw light over an speci c solution that aims to reduce the extra delay produced by these bloated bu ers: Active Queue Management. We have tested a bunch of AQM algorithms with di erent TCP modi cations in order to understand the interactions between these two mechanisms. We performed simulations testing various characteristic scenarios like Transoceanic links or Access link scenarios, among other.Ingeniería Telemátic

Improving video streaming experience through network measurements and analysis

Multimedia traffic dominates today’s Internet. In particular, the most prevalent traffic carried over wired and wireless networks is video. Most popular streaming providers (e.g. Netflix, Youtube) utilise HTTP adaptive streaming (HAS) for video content delivery to end-users. The power of HAS lies in the ability to change video quality in real time depending on the current state of the network (i.e. available network resources). The main goal of HAS algorithms is to maximise video quality while minimising re-buffering events and switching between different qualities. However, these requirements are opposite in nature, so striking a perfect blend is challenging, as there is no single widely accepted metric that captures user experience based on the aforementioned requirements. In recent years, researchers have put a lot of effort into designing subjectively validated metrics that can be used to map quality, re-buffering and switching behaviour of HAS players to the overall user experience (i.e. video QoE). This thesis demonstrates how data analysis can contribute in improving video QoE. One of the main characteristics of mobile networks is frequent throughput fluctuations. There are various underlying factors that contribute to this behaviour, including rapid changes in the radio channel conditions, system load and interaction between feedback loops at the different time scales. These fluctuations highlight the challenge to achieve a high video user experience. In this thesis, we tackle this issue by exploring the possibility of throughput prediction in cellular networks. The need for better throughput prediction comes from data-based evidence that standard throughput estimation techniques (e.g. exponential moving average) exhibit low prediction accuracy. Cellular networks deploy opportunistic exponential scheduling algorithms (i.e. proportional-fair) for resource allocation among mobile users/devices. These algorithms take into account a user’s physical layer information together with throughput demand. While the algorithm itself is proprietary to the manufacturer, physical layer and throughput information are exchanged between devices and base stations. Availability of this information allows for a data-driven approach for throughput prediction. This thesis utilises a machine-learning approach to predict available throughput based on measurements in the near past. As a result, a prediction accuracy with an error less than 15% in 90% of samples is achieved. Adding information from other devices served by the same base station (network-based information) further improves accuracy while lessening the need for a large history (i.e. how far to look into the past). Finally, the throughput prediction technique is incorporated to state-of-the-art HAS algorithms. The approach is validated in a commercial cellular network and on a stock mobile device. As a result, better throughput prediction helps in improving user experience up to 33%, while minimising re-buffering events by up to 85%. In contrast to wireless networks, channel characteristics of the wired medium are more stable, resulting in less prominent throughput variations. However, all traffic traverses through network queues (i.e. a router or switch), unlike in cellular networks where each user gets a dedicated queue at the base station. Furthermore, network operators usually deploy a simple first-in-first-out queuing discipline at queues. As a result, traffic can experience excessive delays due to the large queue sizes, usually deployed in order to minimise packet loss and maximise throughput. This effect, also known as bufferbloat, negatively impacts delay-sensitive applications, such as web browsing and voice. While there exist guidelines for modelling queue size, there is no work analysing its impact on video streaming traffic generated by multiple users. To answer this question, the performance of multiple videos clients sharing a bottleneck link is analysed. Moreover, the analysis is extended to a realistic case including heterogeneous round-trip-time (RTT) and traffic (i.e. web browsing). Based on experimental results, a simple two queue discipline is proposed for scheduling heterogeneous traffic by taking into account application characteristics. As a result, compared to the state-of-the-art Active Queue Management (AQM) discipline, Controlled Delay Management (CoDel), the proposed discipline decreases median Page Loading Time (PLT) of web traffic by up to 80% compared to CoDel, with no significant negative impact on video QoE

Downstream Bandwidth Management for Emerging DOCSIS-based Networks

In this dissertation, we consider the downstream bandwidth management in the context of emerging DOCSIS-based cable networks. The latest DOCSIS 3.1 standard for cable access networks represents a significant change to cable networks. For downstream, the current 6 MHz channel size is replaced by a much larger 192 MHz channel which potentially can provide data rates up to 10 Gbps. Further, the current standard requires equipment to support a relatively new form of active queue management (AQM) referred to as delay-based AQM. Given that more than 50 million households (and climbing) use cable for Internet access, a clear understanding of the impacts of bandwidth management strategies used in these emerging networks is crucial. Further, given the scope of the change provided by emerging cable systems, now is the time to develop and introduce innovative new methods for managing bandwidth. With this motivation, we address research questions pertaining to next generation of cable access networks. The cable industry has had to deal with the problem of a small number of subscribers who utilize the majority of network resources. This problem will grow as access rates increase to gigabits per second. Fundamentally this is a problem on how to manage data flows in a fair manner and provide protection. A well known performance issue in the Internet, referred to as bufferbloat, has received significant attention recently. High throughput network flows need sufficiently large buffer to keep the pipe full and absorb occasional burstiness. Standard practice however has led to equipment offering very large unmanaged buffers that can result in sustained queue levels increasing packet latency. One reason why these problems continue to plague cable access networks is the desire for low complexity and easily explainable (to access network subscribers and to the Federal Communications Commission) bandwidth management. This research begins by evaluating modern delay-based AQM algorithms in downstream DOCSIS 3.0 environments with a focus on fairness and application performance capabilities of single queue AQMs. We are especially interested in delay-based AQM schemes that have been proposed to combat the bufferbloat problem. Our evaluation involves a variety of scenarios that include tiered services and application workloads. Based on our results, we show that in scenarios involving realistic workloads, modern delay-based AQMs can effectively mitigate bufferbloat. However they do not address the other problem related to managing the fairness. To address the combined problem of fairness and bufferbloat, we propose a novel approach to bandwidth management that provides a compromise among the conflicting requirements. We introduce a flow quantization method referred to as adaptive bandwidth binning where flows that are observed to consume similar levels of bandwidth are grouped together with the system managed through a hierarchical scheduler designed to approximate weighted fairness while addressing bufferbloat. Based on a simulation study that considers many system experimental parameters including workloads and network configurations, we provide evidence of the efficacy of the idea. Our results suggest that the scheme is able to provide long term fairness and low delay with a performance close to that of a reference approach based on fair queueing. A further contribution is our idea for replacing `tiered\u27 levels of service based on service rates with tiering based on weights. The application of our bandwidth binning scheme offers a timely and innovative alternative to broadband service that leverages the potential offered by emerging DOCSIS-based cable systems