Adaptive Active Queue Management based on Queue Ratio of Set-point Weighting

Presently, active queue management (AQM) is one of the important considerations in communication networks. The challenge is to make it simple and robust in bursty traffic and uncertain network conditions. This paper proposes a new AQM scheme, an adaptive ratio proportional integral (ARPI), for adaptively controlling network congestion in dynamic network traffic conditions. First, AQM was designed by adding a set-point weighting structure to a proportional integral (PI) controller to reduce the burstiness of network traffic. Second, an adaptive set-point weighting based on the ratio of instantaneous queue length to the set-point queue and the buffer size was proposed to improve the robustness of a non-linear network. The proposed design integrates the aforementioned expectations into one function and needs only one parameter change to adapt to fluctuating network condition. Hence, this scheme provides lightweight computation and simple software and hardware implementation. This approach was analyzed and compared with the PI AQM scheme. Evaluation results demonstrated that our proposed AQM can regulate queue length with a fast response, good stability under any traffic conditions, and small queuing delay

Parameter self-tuning in internet congestion control

Active Queue Management (AQM) aims to achieve high link utilization, low queuing delay and low loss rate in routers. However, it is difficult to adapt AQM parameters to constantly provide desirable transient and steady-state performance under highly dynamic network scenarios. They need to be a trade-off made between queuing delay and utilization. The queue size would become unstable when round-trip time or link capacity increases, or would be unnecessarily large when round-trip time or link capacity decreases. Effective ways of adapting AQM parameters to obtain good performance have remained a critical unsolved problem during the last fifteen years. This thesis firstly investigates existing AQM algorithms and their performance. Based on a previously developed dynamic model of TCP behaviour and a linear feedback model of TCP/RED, Auto-Parameterization RED (AP-RED) is proposed which unveils the mechanism of adapting RED parameters according to measurable network conditions. Another algorithm of Statistical Tuning RED (ST-RED) is developed for systematically tuning four key RED parameters to control the local stability in response to the detected change in the variance of the queue size. Under variable network scenarios like round-trip time, link capacity and traffic load, no manual parameter configuration is needed. The proposed ST-RED can adjust corresponding parameters rapidly to maintain stable performance and keep queuing delay as low as possible. Thus the sensitivity of RED's performance to different network scenarios is removed. This Statistical Tuning algorithm can be applied to a PI controller for AQM and a Statistical Tuning PI (ST-PI) controller is also developed. The implementation of ST-RED and ST-PI is relatively straightforward. Simulation results demonstrate the feasibility of ST-RED and ST-PI and their capabilities to provide desirable transient and steady-state performance under extensively varying network conditions.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Improved congestion control for packet switched data networks and the Internet

Congestion control is one of the fundamental issues in computer networks. Without proper congestion control mechanisms there is the possibility of inefficient utilization of resources, ultimately leading to network collapse. Hence congestion control is an effort to adapt the performance of a network to changes in the traffic load without adversely affecting users perceived utilities. This thesis is a step in the direction of improved network congestion control. Traditionally the Internet has adopted a best effort policy while relying on an end-to-end mechanism. Complex functions are implemented by end users, keeping the core routers of network simple and scalable. This policy also helps in updating the software at the users' end. Thus, currently most of the functionality of the current Internet lie within the end users' protocols, particularly within Transmission Control Protocol (TCP). This strategy has worked fine to date, but networks have evolved and the traffic volume has increased many fold; hence routers need to be involved in controlling traffic, particularly during periods of congestion. Other benefits of using routers to control the flow of traffic would be facilitating the introduction of differentiated services or offering different qualities of service to different users. Any real congestion episode due to demand of greater than available bandwidth, or congestion created on a particular target host by computer viruses, will hamper the smooth execution of the offered network services. Thus, the role of congestion control mechanisms in modern computer networks is very crucial. In order to find effective solutions to congestion control, in this thesis we use feedback control system models of computer networks. The closed loop formed by TCPIIP between the end hosts, through intermediate routers, relies on implicit feedback of congestion information through returning acknowledgements. This feedback information about the congestion state of the network can be in the form of lost packets, changes in round trip time and rate of arrival of acknowledgements. Thus, end hosts can either execute reactive or proactive congestion control mechanisms. The former approach uses duplicate acknowledgements and timeouts as congestion signals, as done in TCP Reno, whereas the latter approach depends on changes in the round trip time, as in TCP Vegas. The protocols employing the second approach are still in their infancy as they cannot co-exist safely with protocols employing the first approach. Whereas TCP Reno and its mutations, such as TCP Sack, are presently widely used in computer networks, including the current Internet. These protocols require packet losses to happen before they can detect congestion, thus inherently leading to wastage of time and network bandwidth. Active Queue Management (AQM) is an alternative approach which provides congestion feedback from routers to end users. It makes a network to behave as a sensitive closed loop feedback control system, with a response time of one round trip time, congestion information being delivered to the end host to reduce data sending rates before actual packets losses happen. From this congestion information, end hosts can reduce their congestion window size, thus pumping fewer packets into a congested network until the congestion period is over and routers stop sending congestion signals. Keeping both approaches in view, we have adopted a two-pronged strategy to address the problem of congestion control. They are to adapt the network at its edges as well as its core routers. We begin by introducing TCPIIP based computer networks and defining the congestion control problem. Next we look at different proactive end-to-end protocols, including TCP Vegas due to its better fairness properties. We address the incompatibility problem between TCP Vegas and TCP Reno by using ECN based on Random Early Detection (RED) algorithm to adjust parameters of TCP Vegas. Further, we develop two alternative algorithms, namely optimal minimum variance and generalized optimal minimum variance, for fair end-to-end protocols. The relationship between (p, 1) proportionally fair algorithm and the generalized algorithm is investigated along with conditions for its stable operation. Noteworthy is a novel treatment of the issue of transient fairness. This represents the work done on congestion control at the edges of network. Next, we focus on router-based congestion control algorithms and start with a survey of previous work done in that direction. We select the RED algorithm for further work due to it being recommended for the implementation of AQM. First we devise a new Hybrid RED algorithm which employs instantaneous queue size along with an exponential weighted moving average queue size for making decisions about packet marking/dropping, and adjusts the average value during periods of low traffic. This algorithm improves the link utilization and packet loss rate as compared to basic RED. We further propose a control theory based Auto-tuning RED algorithm that adapts to changing traffic load. This algorithm can clamp the average queue size to a desired reference value which can be used to estimate queuing delays for Quality of Service purposes. As an alternative approach to router-based congestion control, we investigate Proportional, Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) principles based control algorithms for AQM. New control-theoretic RED and frequency response based PI and PID control algorithms are developed and their performance is compared with that of existing algorithms. Later we transform the RED and PI principle based algorithms into their adaptive versions using the well known square root of p formula. The performance of these load adaptive algorithms is compared with that of the previously developed fixed parameter algorithms. Apart from some recent research, most of the previous efforts on the design of congestion control algorithms have been heuristic. This thesis provides an effective use of control theory principles in the design of congestion control algorithms. We develop fixed-parameter-type feedback congestion control algorithms as well as their adaptive versions. All of the newly proposed algorithms are evaluated by using ns-based simulations. The thesis concludes with a number of research proposals emanating from the work reported

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

Router-based network traffic observation by terminal sliding mode control theory

Since the early days of the Internet, network traffic monitoring (NTM) has always played a strategic role in understanding and characterizing users’ activities. Nowadays, with the increased complexity of the Internet infrastructure, applications, and services, this role has become more crucial than ever. The aims of NTM are mainly focused on the three improvements, which include the quality of service (QoS) of the network, optimization of resource usage, and enhancement of security in computer networks. Specifically speaking, firstly, network conditions can be recognized by the network manager with NTM scheme. It provides the complete details about the QoS of networks, such as bandwidth, throughput, propagation delay, link availability, jitter, server memory, database space and etc. Secondly, with NTM being implemented at network nodes, i.e., network gateways, such as routers, or network links, the network traffic that is traversing the network is under online observation. Thereby, the network utilization can be improved by optimizing the resource usage to avoid the network congestions. Thirdly, unauthenticated service or approaches to the server will be identified by regularly monitoring the traffic. The network convention and statistics about the traffic will be known easily which helps to troubleshoot the network. Security events will also be investigated and the entry of the user will be maintained for responsibility. The work in this thesis focuses on the development of an intelligent real-time dynamic router-based network traffic observation (RNTO) by using the terminal sliding-mode theory. The RNTO technique is applied at network gateways, i.e., routers, to estimate the status of the traffic flows at the router level. The aims of the proposed RNTO technique is to estimate the traffic states, such as queue length (QL)in router buffer, average congestion window size (ACwnd), and the queuing dynamics of the additional traffic flows (ATF). The main contributions of the work can be broadly categorized into four parts. First, the problem of router-based network traffic monitoring is formulated as an observer design by using TSM theory for RNTO applications. The proposed TSM observer in the research is a network-based monitoring, which is implemented into the network gateways, i.e., network routers. Different from the static network traffic monitoring methods, the TSM observer is designed by using control methods based on the fluid-flow mathematical model, which represents the traffic dynamics of the interactions in a set of TCP traffic flows through network routers. By considering the time delay and stochastic properties in the data transmission network, the sliding-mode observation strategy is proposed with its high robustness with system parameter uncertainties as well as the external disturbance rejection. Given the natural weakness of chattering in sliding mode control signal, which can affect the system state, the chattering avoiding technique of the proposed TSM observation was utilized by using a smooth control signal for estimating the abnormal dynamics. It does not need any low-pass filler, which will lead to a phase leg. In addition, for the stochastic dynamics of the network traffics, fast transient convergence at a distance from and within a close range of the equilibrium of the traffic dynamics is essential to quickly capture traffic dynamics in network systems. Thus, a fractional term has been considered in the TSM for faster convergence in system states to efficiently estimate the traffic behaviors. Second, the issue of internal dynamics in network observation system is studied by proposing a novel full-order TSM strategy to speed up the convergence rate of the estimation error. In the RNTO scheme, the precise estimation for ACwnd is needed to estimate the queuing dynamics of ATF. However, the estimation error for ACwnd is not available and it converges to origin asymptotically, which results in a long response time in estimation. The proposed novel TSM observer has been designed to drive the estimation error for ACwnd to a defined known area in the finite-time, which can be calculated. Thereby, the estimation error of ACwnd can converge to origin asymptotically within the defined area. This strategy has shortened the response time and improves the estimation accuracy. This further improves the estimation accuracy for ATF. The comparative studies are conducted to evaluate the performance. Third, the issue of algorithm-efficient RNTO is investigated by considering an event triggered sliding-mode observer to reduce the computational load and the communication burden. Instead of the time-driven observation scheme, the control of the sliding mode observer is formulated under the event triggered scheme. The control of the observer is designed to be smooth and is directly applied to estimate the dynamics of the additional traffic flows. The event triggered observation algorithms is developed to reduce the computational load of the network router and the communication resource of output link in the network. Fourth, the problem of global RNTO is addressed by developing a fuzzy TSM observer by using fuzzy theory to achieve global operation under network uncertainties. The existing RNTO schemes are based on the linearization of a certain network conditions, i.e., a fixed number of TCP connections, which is a constant value N. Given the network suffers from time-varying fading, shadowing and interference and the data rate changes over time, the current methods proposed so far might not effectively and accurately monitor and estimate the traffic dynamics under network uncertainties. The T-S fuzzy models are used to model the traffic dynamics of the time-varying data changes in network link resources, i.e. the time-varying number of TCP sections, N(t) in a mathematical model. Based on the T-S fuzzy models, the fuzzy terminal sliding mode observer is established by using the fuzzy logic theory to estimate the states of the network traffic to achieve the global observation performance under the network uncertainties. In the fuzzy terminal sliding mode observer, the control signal is designed to be continuous for application of estimating the additional traffic flows without the low-pass filter. To evaluate the proposed RNTO technique, the networking simulator tool Network Simulator II (NS-II) has been used. The proposed RNTO algorithms are coded and implemented into network routers in NS-II. Numerous simulation scenarios are considered and performed. The comparative studies are also conducted by analyzing the NS-2 results. The results have demonstrated the effectiveness and efficiency of the proposed RNTO algorithms

SON/RRM Functionality for mobility load balancing in LTE networks

Implementation and Analysis of a Mobility Load Balancing Algorithm base on the adjustment of mobility parameters. This functionality of Self-Optimization belongs to the proposed solution fon Self-Organizing Networks from the 3GPP for LTE Networks.Implementación y Análisis de un algoritmo Balanceador de carga basado en el cambio de los parámetros de movilidad. Esta funcionalidad de auto-optimización pertenece a las soluciones aconsejadas en redes auto-organizadas del 3GPP para redes LTE.Navarro Suria, S. (2013). SON/RRM Functionality for mobility load balancing in LTE networks. http://hdl.handle.net/10251/29044.Archivo delegad

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017