A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

HFAQM: A hybrid fair active queue management mechanism to improve fairness and stability for wireless local area network

Active Queue Management (AQM) is a proactive scheme that controls network congestion by avoiding it before it happens. When implementing AQM in wireless networks, several contemporary issues must be considered, such as interference, collisions, multipath-fading, propagation distance and shadowing effects, which affect the transmission rate of the links. These issues in WLAN networks with the existence of different types of flow have a direct effect on fairness. The main idea behind the wireless network is using the flexibility of radio waves to transfer data from point to point that is giving WLAN the flexibility and mobility: wireless nodes can connect, disconnect or even move from one access point to another rapidly. However, this affects the stability of the WLAN network. This research aims to reduce unfairness and instability by proposing a Hybrid-Fair AQM (HFAQM) scheme. HFAQM comprises two mechanisms: Congestion Indicator Mechanism (CIM), and Control Function Mechanism (CFM). CIM was designed to improve fairness in WLANs by hybridizing queue delay with arrival rate as parameters to calculate the congestion level. Whereas, CFM was developed to improve network stability by using an adaptive control function with the ability to drop and mark packets to overcome the rapidly changing characteristics of WLAN network. A series of experimental studies were conducted to validate the proposed mechanisms and four variants of AQM schemes, RED, REM, AVQ and CoDel, were chosen to evaluate the performance of HFAQM through simulation. The findings show that HFAQM’s main achievement is 99% fairness and improved stability by 10% from the closest scheme, with better throughput, queue length, queue loss, and outgoing link utilization as secondary achievements. The proposed scheme provides significantly better fairness and stability in WLAN environment, with the existence of different types of flow

Discrete-time queueing model for responsive network traffic and bottleneck queues

The Internet has been more and more intensively used in recent years. Although network infrastructure has been regularly upgraded, and the ability to manage heavy traffic greatly increased, especially on the core networks, congestion never ceases to appear, as the amount of traffic that flow on the Internet seems to be increasing at an even faster rate. Thus, congestion control mechanisms play a vital role in the functioning of the Internet. Active Queue Management (AQM) is a popular type of congestion control mechanism that is implemented on gateways (most notably routers), which can predict and avoid the congestion before it happens. When properly configured, AQMs can effectively reduce the congestion, and alleviate some of the problems such as global synchronisation and unfairness to bursty traffic. However, there are still many problems regarding AQMs. Most of the AQM schemes are quite sensitive to their parameters setting, and these parameters may be heavily dependent on the network traffic profile, which the administrator may not have intensive knowledge of, and is likely to change over time. When poorly configured, many AQMs perform no better than the basic drop-tail queue. There is currently no effective method to compare the performance of these AQM algorithms, caused by the parameter configuration problem. In this research, the aim is to propose a new analytical model, which mainly uses discrete-time queueing theory. A novel transient modification to the conventional equilibrium-based method is proposed, and it is utilised to further develop a dynamic interactive model of responsive traffic and bottleneck queues. Using step-by-step analysis, it represents the bursty traffic and oscillating queue length behaviour in practical network more accurately. It also provides an effective way of predicting the behaviour of a TCP-AQM system, allowing easier parameter optimisation for AQM schemes. Numerical solution using MATLAB and software simulation using NS-2 are used to extensively validate the proposed models, theories and conclusions

TCP performance enhancement in wireless networks via adaptive congestion control and active queue management

The transmission control protocol (TCP) exhibits poor performance when used in error-prone wireless networks. Remedy to this problem has been an active research area. However, a widely accepted and adopted solution is yet to emerge. Difficulties of an acceptable solution lie in the areas of compatibility, scalability, computational complexity and the involvement of intermediate routers and switches. This dissertation rexriews the current start-of-the-art solutions to TCP performance enhancement, and pursues an end-to-end solution framework to the problem. The most noticeable cause of the performance degradation of TCP in wireless networks is the higher packet loss rate as compared to that in traditional wired networks. Packet loss type differentiation has been the focus of many proposed TCP performance enhancement schemes. Studies conduced by this dissertation research suggest that besides the standard TCP\u27s inability of discriminating congestion packet losses from losses related to wireless link errors, the standard TCP\u27s additive increase and multiplicative decrease (AIMD) congestion control algorithm itself needs to be redesigned to achieve better performance in wireless, and particularly, high-speed wireless networks. This dissertation proposes a simple, efficient, and effective end-to-end solution framework that enhances TCP\u27s performance through techniques of adaptive congestion control and active queue management. By end-to-end, it means a solution with no requirement of routers being wireless-aware or wireless-specific . TCP-Jersey has been introduced as an implementation of the proposed solution framework, and its performance metrics have been evaluated through extensive simulations. TCP-Jersey consists of an adaptive congestion control algorithm at the source by means of the source\u27s achievable rate estimation (ARE) —an adaptive filter of packet inter-arrival times, a congestion indication algorithm at the links (i.e., AQM) by means of packet marking, and a effective loss differentiation algorithm at the source by careful examination of the congestion marks carried by the duplicate acknowledgment packets (DUPACK). Several improvements to the proposed TCP-Jersey have been investigated, including a more robust ARE algorithm, a less computationally intensive threshold marking algorithm as the AQM link algorithm, a more stable congestion indication function based on virtual capacity at the link, and performance results have been presented and analyzed via extensive simulations of various network configurations. Stability analysis of the proposed ARE-based additive increase and adaptive decrease (AJAD) congestion control algorithm has been conducted and the analytical results have been verified by simulations. Performance of TCP-Jersey has been compared to that of a perfect , but not practical, TCP scheme, and encouraging results have been observed. Finally the framework of the TCP-Jersey\u27s source algorithm has been extended and generalized for rate-based congestion control, as opposed to TCP\u27s window-based congestion control, to provide a design platform for applications, such as real-time multimedia, that do not use TCP as transport protocol yet do need to control network congestion as well as combat packet losses in wireless networks. In conclusion, the framework architecture presented in this dissertation that combines the adaptive congestion control and active queue management in solving the TCP performance degradation problem in wireless networks has been shown as a promising answer to the problem due to its simplistic design philosophy complete compatibility with the current TCP/IP and AQM practice, end-to-end architecture for scalability, and the high effectiveness and low computational overhead. The proposed implementation of the solution framework, namely TCP-Jersey is a modification of the standard TCP protocol rather than a completely new design of the transport protocol. It is an end-to-end approach to address the performance degradation problem since it does not require split mode connection establishment and maintenance using special wireless-aware software agents at the routers. The proposed solution also differs from other solutions that rely on the link layer error notifications for packet loss differentiation. The proposed solution is also unique among other proposed end-to-end solutions in that it differentiates packet losses attributed to wireless link errors from congestion induced packet losses directly from the explicit congestion indication marks in the DUPACK packets, rather than inferring the loss type based on packet delay or delay jitter as in many other proposed solutions; nor by undergoing a computationally expensive off-line training of a classification model (e.g., HMM), or a Bayesian estimation/detection process that requires estimations of a priori loss probability distributions of different loss types. The proposed solution is also scalable and fully compatible to the current practice in Internet congestion control and queue management, but with an additional function of loss type differentiation that effectively enhances TCP\u27s performance over error-prone wireless networks. Limitations of the proposed solution architecture and areas for future researches are also addressed

Dynamics of TCP/RED and a Scalable Control

We demonstrate that the dynamic behavior of queue and average window is determined predominantly by the stability of TCP/RED, not by AIMD probing nor noise traffic. We develop a general multi-link multi-source model for TCP/RED and derive a local stability condition in the case of a single link with heterogeneous sources. We validate our model with simulations and illustrate the stability region of TCP/RED. These results suggest that TCP/RED becomes unstable when delay increases, or more strikingly, when link capacity increases. The analysis illustrates the difficulty of setting RED parameters to stabilize TCP: they can be tuned to improve stability, but only at the cost of large queues even when they are dynamically adjusted. Finally, we present a simple distributed congestion control algorithm that maintains stability for arbitrary network delay, capacity, load and topology

A multi-objective particle swarm optimized fuzzy logic congestion detection and dual explicit notification mechanism for IP networks.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2006.The Internet has experienced a tremendous growth over the past two decades and with that growth have come severe congestion problems. Research efforts to alleviate the congestion problem can broadly be classified into three groups: Cl) Router based congestion detection; (2) Generation and transmission of congestion notification signal to the traffic sources; (3) End-to-end algorithms which control the flow of traffic between the end hosts. This dissertation has largely addressed the first two groups which are basically router initiated. Router based congestion detection mechanisms, commonly known as Active Queue Management (AQM), can be classified into two groups: conventional mathematical analytical techniques and fuzzy logic based techniques. Research has shown that fuzzy logic techniques are more effective and robust compared to the conventional techniques because they do not rely on the availability of a precise mathematical model of Internet. They use linguistic knowledge and are, therefore, better placed to handle the complexities associated with the non-linearity and dynamics of the Internet. In spite of all these developments, there still exists ample room for improvement because, practically, there has been a slow deployment of AQM mechanisms. In the first part of this dissertation, we study the major AQM schemes in both the conventional and the fuzzy logic domain in order to uncover the problems that have hampered their deployment in practical implementations. Based on the findings from this study, we model the Internet congestion problem as a multi-objective problem. We propose a Fuzzy Logic Congestion Detection (FLCD) which synergistically combines the good characteristics of the fuzzy approaches with those of the conventional approaches. We design the membership functions (MFs) of the FLCD algorithm automatically by using Multi-objective Particle Swarm Optimization (MOPSO), a population based stochastic optimization algorithm. This enables the FLCD algorithm to achieve optimal performance on all the major objectives of Internet congestion control. The FLCD algorithm is compared with the basic Fuzzy Logic AQM and the Random Explicit Marking (REM) algorithms on a best effort network. Simulation results show that the FLCD algorithm provides high link utilization whilst maintaining lower jitter and packet loss. It also exhibits higher fairness and stability compared to its basic variant and REM. We extend this concept to Proportional Differentiated Services network environment where the FLCD algorithm outperforms the traditional Weighted RED algorithm. We also propose self learning and organization structures which enable the FLCD algorithm to achieve a more stable queue, lower packet losses and UDP traffic delay in dynamic traffic environments on both wired and wireless networks. In the second part of this dissertation, we present the congestion notification mechanisms which have been proposed for wired and satellite networks. We propose an FLCD based dual explicit congestion notification algorithm which combines the merits of the Explicit Congestion Notification (ECN) and the Backward Explicit Congestion Notification (BECN) mechanisms. In this proposal, the ECN mechanism is invoked based on the packet marking probability while the BECN mechanism is invoked based on the BECN parameter which helps to ensure that BECN is invoked only when congestion is severe. Motivated by the fact that TCP reacts to tbe congestion notification signal only once during a round trip time (RTT), we propose an RTT based BECN decay function. This reduces the invocation of the BECN mechanism and resultantly the generation of reverse traffic during an RTT. Compared to the traditional explicit notification mechanisms, simulation results show that the new approach exhibits lower packet loss rates and higher queue stability on wired networks. It also exhibits lower packet loss rates, higher good-put and link utilization on satellite networks. We also observe that the BECN decay function reduces reverse traffic significantly on both wired and satellite networks while ensuring that performance remains virtually the same as in the algorithm without BECN traffic reduction.Print copy complete; page numbering of 105-108 incorrect

Performance modelling and analysis of congestion control mechanisms for communication networks with quality of service constraints. An investigation into new methods of controlling congestion and mean delay in communication networks with both short range dependent and long range dependent traffic.

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that haveMinistry of Higher Education in Egypt and the Egyptian Cultural Centre and Educational Bureau in Londo

Stabilizing RED queue oscillation using the logistic map in AutoRED mechanism

Active queue management (AQM) is one of the ways to control congestion at Internet Routers. One of the widely used AQM's is the random early detection (RED) scheme. The RED scheme suffers from chaotic queue oscillation problem particularly in a highly congested network. It causes jitter, high queuing delay when the queue size stays high, and underutilization when the queue size is low. Recently AutoRED algorithm has been proposed as a solution to the chaotic queue oscillation problem in that AutoRED calculates the weight, wq, continuously as opposed to a constant value set by a user [1]. AutoRED displays the reduction of the chaotic queue oscillation by network performance metrics and queue behavior graphs, but there has been no metric known to measure the degree of queue oscillation in terms of its effect on the Quality of Service (QoS). The purpose of the present study is twofold. Firstly, the possibility of an improvement by modifying AutoRED using a Logistic Map is investigated. This new technique introduces a user control parameter that can contribute to further improvements. Secondly, a new metric is proposed to show the degree of queue oscillation with regards to its effect on the QoS. The experiments are done by applying the new technique to network simulations in TCP only and TCP and UDP combined traffic environments. The results are compared with RED and AutoRED with regards to the proposed metric coupled with the network performance measurements and the statistical measurements of the queue behavior

An efficient pending interest table control management in named data network

Named Data Networking (NDN) is an emerging Internet architecture that employs a new network communication model based on the identity of Internet content. Its core component, the Pending Interest Table (PIT) serves a significant role of recording Interest packet information which is ready to be sent but in waiting for matching Data packet. In managing PIT, the issue of flow PIT sizing has been very challenging due to massive use of long Interest lifetime particularly when there is no flexible replacement policy, hence affecting PIT performance. The aim of this study is to propose an efficient PIT Control Management (PITCM) approach to be used in handling incoming Interest packets in order to mitigate PIT overflow thus enhancing PIT utilization and performance. PITCM consists of Adaptive Virtual PIT (AVPIT) mechanism, Smart Threshold Interest Lifetime (STIL) mechanism and Highest Lifetime Least Request (HLLR) policy. The AVPIT is responsible for obtaining early PIT overflow prediction and reaction. STIL is meant for adjusting lifetime value for incoming Interest packet while HLLR is utilized for managing PIT entries in efficient manner. A specific research methodology is followed to ensure that the work is rigorous in achieving the aim of the study. The network simulation tool is used to design and evaluate PITCM. The results of study show that PITCM outperforms the performance of standard NDN PIT with 45% higher Interest satisfaction rate, 78% less Interest retransmission rate and 65% less Interest drop rate. In addition, Interest satisfaction delay and PIT length is reduced significantly to 33% and 46%, respectively. The contribution of this study is important for Interest packet management in NDN routing and forwarding systems. The AVPIT and STIL mechanisms as well as the HLLR policy can be used in monitoring, controlling and managing the PIT contents for Internet architecture of the future