Active Queue Management Mechanism Research Articles

RED-SP-CoDel: Random early detection with static priority scheduling and controlled delay AQM in programmable data planes

Emerging network application paradigms, such as the Tactile Internet, re-emphasize the need for different Quality of Service (QoS) levels. Due to the large packet buffers in the underlying network data plane, Active Queue Management (AQM) is generally required to curtail packet latencies for flows requiring high QoS levels. At the same time, programmable data planes, such as P4, enable packet processing at line-speed, albeit with limited packet processing functionalities. However, the existing AQM mechanisms that support QoS differentiation are too complex to readily run on P4, while the existing AQM mechanisms that run on P4 do generally not support effective QoS differentiation. We address this gap by developing to the best of our knowledge the first AQM mechanism that supports effective QoS differentiation while running on P4. Specifically, we propose SP-CoDel, which combines the well-known Controlled Delay (CoDel) AQM mechanism with Static Priority (SP) scheduling for QoS differentiation. Also, we propose RED-SP-CoDel, which adds a RED AQM component to SP-CoDel so as to make the AQM with priorities essentially parameterless. As a community resource contribution, we substantially extend the existing P4Simulator to the novel fused P4-NS3 Simulator so as to enable the evaluation of packet processing mechanisms through the combined functionalities of P4 device emulation and NS3 packet simulation. Evaluations conducted with the P4 reference switch model in the P4-NS3 Simulator indicate that SP-CoDel and RED-SP-CoDel provide high QoS to high-priority data streams, i.e., significantly reduce latency and packet loss compared to CoDel, while effectively mitigating bufferbloat.

R-AQM: Reverse ACK Active Queue Management in Multitenant Data Centers

TCP incast has become a practical problem for high-bandwidth, low-latency transmissions, resulting in throughput degradation of up to 90% and delays of hundreds of milliseconds, severely impacting application performance. However, in virtualized multi-tenant data centers, host-based advancements in the TCP stack are hard to deploy from the operators’ perspective. Operators only provide infrastructure in the form of virtual machines, in which only tenants can directly modify the end-host TCP stack. In this paper, we present R-AQM, a switch-powered reverse ACK active queue management (R-AQM) mechanism for enhancing ACK-clocking effects through assisting legacy TCP. Specifically, R-AQM proactively intercepts ACKs and paces the ACK-clocked in-flight data packets, preventing TCP from suffering incast collapse. We implement and evaluate R-AQM in NS-3 simulation and NetFPGA-based hardware switch. Both simulation and testbed results show that R-AQM greatly improves TCP performance under heavy incast workloads by significantly lowering packet loss rate, reducing retransmission timeouts, and supporting 16 times (i.e., 60 to 1000) more senders. Meanwhile, the forward queuing delays are also reduced by 4.6 times.

On the Influence of AQM on Serialization of Packet Losses.

We study the influence of the active queue management mechanism based on the queue size on the serialization of packet losses, i.e., the occurrences of losses in long, consecutive series. We use a traffic model able to mimic precisely the autocorrelation function of traffic, which is known to be far from zero in packet networks. The main contribution is a theorem on the burst ratio parameter, describing the serialization of losses, proven for an arbitrary function assigning drop probabilities to queue sizes. In numerical examples, we show the impact of the autocorrelation strength, drop probability function, and load of the link, on the serialization of losses.

New RED-Type TCP-AQM Algorithms Based on Beta Distribution Drop Functions

In recent years, Active Queue Management (AQM) mechanisms to improve the performance of TCP/IP networks have acquired a relevant role. In this paper, we present a simple and robust RED-type algorithm together with a couple of dynamical variants with the ability to adapt to the specific characteristics of different network environments, as well as to the user’s needs. We first present a basic version called Beta RED (BetaRED), where the parameters can be tuned according to the specific network conditions. The aim is to introduce control parameters that are easy to interpret and provide a good performance over a wide range of values. Secondly, BetaRED is used as a framework to design two dynamic algorithms, which we will call Adaptive Beta RED (ABetaRED) and Dynamic Beta RED (DBetaRED). In those new algorithms, certain parameters are dynamically adjusted so that the queue length remains stable around a predetermined reference value and according to changing network traffic conditions. Finally, we present a battery of simulations using the Network Simulator 3 (ns-3) software with a two-fold objective: to guide the user on how to adjust the parameters of the BetaRED mechanism, and to show a performance comparison of ABetaRED and DBetaRED with other representative algorithms that pursue a similar objective.

Finite capacity single-server queue with Poisson input, general service and delayed renovation

This paper is devoted to the performance evaluation of the finite–capacity single-server queue with Poisson input and general service times, which is equipped with the novel queue-control mechanism — called renovation with delay. Renovation implies that each customer, when leaving the system upon its service completion, may also remove customers waiting in the queue. The number of customers to be removed is selected each time independently of the previous decisions and probabilistically based on the given probability distribution. The renovation with the delay considered in this paper means that the system must accumulate the (known) fixed number of service completions before the next renovation can be triggered. First in the literature numerical evidence is given, that the long-run performance of the system with such delayed renovation mechanism can be similar to that of the systems with the well-known active queue management mechanisms such as random early detection, at least in its basic version. The key stationary performance characteristics reported are the loss probability and the mean number of customers in the system. The unified analytical framework for the computation of the key performance characteristics, which is of independent interest, is also developed.

Adaptive Hurst-Sensitive Active Queue Management.

An Active Queue Management (AQM) mechanism, recommended by the Internet Engineering Task Force (IETF), increases the efficiency of network transmission. An example of this type of algorithm can be the Random Early Detection (RED) algorithm. The behavior of the RED algorithm strictly depends on the correct selection of its parameters. This selection may be performed automatically depending on the network conditions. The mechanisms that adjust their parameters to the network conditions are called the adaptive ones. The example can be the Adaptive RED (ARED) mechanism, which adjusts its parameters taking into consideration the traffic intensity. In our paper, we propose to use an additional traffic parameter to adjust the AQM parameters—degree of self-similarity—expressed using the Hurst parameter. In our study, we propose the modifications of the well-known AQM algorithms: ARED and fractional order and the algorithms based on neural networks that are used to automatically adjust the AQM parameters using the traffic intensity and its degree of self-similarity. We use the Fluid Flow approximation and the discrete event simulation to evaluate the behavior of queues controlled by the proposed adaptive AQM mechanisms and compare the results with those obtained with their basic counterparts. In our experiments, we analyzed the average queue occupancies and packet delays in the communication node. The obtained results show that considering the degree of self-similarity of network traffic in the process of AQM parameters determination enabled us to decrease the average queue occupancy and the number of rejected packets, as well as to reduce the transmission latency.

Supervised Learning of Neural Networks for Active Queue Management in the Internet.

The paper examines the AQM mechanism based on neural networks. The active queue management allows packets to be dropped from the router’s queue before the buffer is full. The aim of the work is to use machine learning to create a model that copies the behavior of the AQM mechanism. We create training samples taking into account the self-similarity of network traffic. The model uses fractional Gaussian noise as a source. The quantitative analysis is based on simulation. During the tests, we analyzed the length of the queue, the number of rejected packets and waiting times in the queues. The proposed mechanism shows the usefulness of the Active Queue Management mechanism based on Neural Networks.

Queueing systems with different types of renovation mechanism and thresholds as the mathematical models of active queue management mechanism

This article is devoted to some aspects of using the renovation mechanism (different types of renovation are considered, definitions and brief overview are also given) with one or several thresholds as the mathematical models of active queue management mechanisms. The attention is paid to the queuing systems in which a threshold mechanism with renovation is implemented. This mechanism allows to adjust the number of packets in the system by dropping (resetting) them from the queue depending on the ratio of a certain control parameter with specified thresholds at the moment of the end of service on the device (server) (in contrast to standard RED-like algorithms, when a possible drop of a packet occurs at the time of arrivals of next packets in the system). The models with one, two and three thresholds with different types of renovation are under consideration. It is worth noting that the thresholds determine not only from which place in the buffer the packets are dropped, but also to which the reset of packets occurs. For some of the models certain analytical and numerical results are obtained (the references are given), some of them are only under investigation, so only the mathematical model and current results may be considered. Some results of comparing classic RED algorithm with renovation mechanism are presented.

Combined diffusion approximation–simulation model of AQM’s transient behavior

The article introduces an approach combining diffusion approximation and simulation ones. Furthermore, it describes how it can be used to evaluate active queue management (AQM) mechanisms. Based on the obtained queue distributions, the simulation part of the model decides on package losses and modifies the flow intensity sent by the transmitter. The diffusion is used to estimate queue distributions and the goal of the simulation part of the model is to represent the AQM mechanism. On the one hand, the use of the diffusion part considerably accelerates the performance of the whole model. On the other hand, the simulation increases the accuracy of the diffusion part. We apply the model to compare the performance of fractional order PIη controller used in AQM with the performance of RED, a well known active queue management mechanism.

Congestion Control Mechanism Based on Dual Threshold DI-RED for WSNs

In wireless sensor networks (WSNs), traffic flow congestion can reduce network performance. We propose a congestion control method for WSNs that use a cache state with a dual threshold in the router buffer to control congestion. In addition, the congestion is controlled by the channel transmission state that is monitored by the queuing variation tendency and the transmission rate. Based on the active queue management mechanism, a dual threshold with the double index random early detection (DI-RED) model is established to improve network performance. We also present the congestion control algorithm of DI-RED model to ensure the perfect actualization. By solving the DI-RED model, a series of channel indicators is obtained, including packet loss rate, average queue length, delay and throughput. Simulation results show that the proposed DI-RED model is more stable and demonstrates better control, which can overcome the parameter sensitivity of the RED mechanism. The proposed model realises a reasonable tradeoff between network performance and packet dropping probability, which effectively avoids degraded network performance caused by pursuing a lower packet dropping probability. The results are important when selecting a congestion control mechanism and parameter settings for WSNs.

Interval type-2 and type-1 Fuzzy Logic Controllers for congestion avoidance in internet routers

Active queue management (AQM) scheme is an important research area in congestion control. The AQM mechanism attains the congestion controller by regularize the length of queue from evaluation or dropping the packets at the moderate routers. In this paper the interval type-2 and type-1 fuzzy logic controller are designed to desist the congestion in the networks. Several evolutionary optimization algorithms are used to select the parameters of two controllers as particle swarm optimization (PSO), social spider optimization (SSO) and ant colony Optimization (ACO). The simulation of linearized model of TCP/AQM are introduced in MATLAB (R2018a). Results of the PID like fuzzy type-1controller is compared with PID like interval type-2 fuzzy controller (IT2-FLC) based on optimization algorithms in each controller and shows that IT2-FLC with SSO has been given the best result.

Diffusion Approximation Model of TCP NewReno Congestion Control Mechanism

The aim of the article is to contribute to the modeling and evaluation of TCP/IP traffic control in case of active queue management mechanisms implemented in congestion router. We consider mechanisms based on RED and fractional-order PI^alpha controller. A new model based on diffusion approximation is developed and its results are compared with the results of an existing fluid flow model. Both models are used to investigate the influence of AQM control parameters on the flow control. Their numerical results concerning dynamics of congestion widow, loss probability, and traffic changes are quite similar. The advantage of the new model lies in giving more detailed information: the distribution of router queue and the distribution of introduced delay, not only their mean values as it is in case of fluid flow model. The variability of transmission time (jitter) is a factor of transmission quality, and therefore, the proposed model may be useful in further studies on TCP/IP quality of service.

Hybrid Fuzzy Congestion Controllers for Computer Networks Tuned by Modified Particle Swarm Optimization

One of the most debated issues nowadays is the quality of computer network service. The best internet service must provide a fast processing of the traffic. Each router has a queue of packets that provides a buffer space, where the packets wait for processing. Transmission Control Protocol (TCP) is a packets congestion control theory. Active Queue Management (AQM) is a mechanisms proposed to employ at gateways to improve the performance of TCP congestion control. AQM mechanisms aim to provide high link utilization with low loss rate and low queuing delay while reacting to load changes quickly. Random Early Detection (RED) is an extensively studied AQM algorithm that can detect congestion by dropping packets randomly with certain probability that serves as the function of the average queue size. In this work, hybrids Fuzzy Logic Controllers (FLC) are proposed to measure the router queue size directly by use them as a congestion controllers. A multiple hybrid fuzzy controllers are proposed, where (Proportional Integral Derivative controller (PID) -like FLC-Particle Swarm Optimization (PSO) Based, Proportional Derivative (PD)-like FLC with conventional I-PSO Based and PID tuned by Fuzzy Logic-PSO Based), which is provided to regulate the queue length, round trip time and packet loss. The Particle Swarmed Optimization (PSO) algorithm is used for tuning the gains of hybrid fuzzy logic controller which helps in reducing the error of the queue size. This is achieved through minimizing the rise time, peak time, settling time and overshoot of the AQM response. The empirical results revealed a high-performance improvement regarding the proposed method in comparison to previous works of other researchers.

The use of a non-integer order PI controller with an active queue management mechanism

Abstract In this paper the performance of a fractional order PI controller is compared with that of RED, a well-known active queue management (AQM) mechanism. The article uses fluid flow approximation and discrete-event simulation to investigate the influence of the AQM policy on the packet loss probability, the queue length and its variability. The impact of self-similar traffic is also considered.

AQM과 ECN을 사용한 TCP 변종의 성능 분석

Transmission Control Protocol as a transport layer protocol provides steady data transfer service. There are some serious concerns about the performance of TCP over diverse networks. The vital concern in TCP network environment is congestion which may occur due to quick transmission rates or because of large number of new connections entering the network at the same time. Size of queues in routers grows thus resulting in packet drops. Retransmission of the dropped packets, and reduced throughput can prove costly. Explicit Congestion Notification (ECN) in conjunction with Active Queue Management mechanisms (AQM) such as Random early detection (RED) is used for packet marking rather than dropping. In IP packet header ECN bits can be added as a sign of congestion thus avoiding needless packet drops. The proposed ECN and AQM mechanism can be implemented with help of ns2 simulator and the performance can be tested on different TCP variants.

Active Queue Management Mechanisms and its Effects on Voice over IP

Active Queue Management Mechanisms and its Effects on Voice over IP

TCP and Network Coding: Equilibrium and Dynamic Properties

This paper analyzes the impact on the stability of the TCP-Reno congestion control mechanism when a network coding (NC) layer is inserted in the TCP/IP stack. A model of the dynamics of the TCP-NC protocol combined with random early detection (RED) as active queue management mechanism is considered to study the network equilibrium and stability properties. The existence and uniqueness of an equilibrium point is demonstrated and characterized in terms of average throughput, loss rate, and queue length. Global stability is proved in absence of forward delay, and the effects of the NC redundancy factor and of the delay on the local stability of TCP-NC-RED are studied around the equilibrium. The fairness of TCP-NC with respect to TCP-Reno-like protocols is also studied. A version of TCP-NC with adaptive redundancy factor (TCP-NCAR) is also introduced. Results provided by the proposed model are compared to those obtained by simulation for $N$ sources sharing a single link. TCP-NC-RED becomes unstable when delay or capacity increases, as TCP-Reno does, but also when the redundancy factor increases. Its stability region is characterized as a function of the redundancy factor. If TCP-NC and TCP-Reno share the same links, TCP-NC is fair with TCP-Reno-like protocols when no redundancy is added. Simulations show that TCP-NCAR is able to compensate losses on the wireless parts of the network.

Some Improvements on Active Queue Management Mechanism Based on Adaptive Fuzzy Control

Some Improvements on Active Queue Management Mechanism Based on Adaptive Fuzzy Control

Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily

Fuzzy Neuro Approach for Active Queue Management

Out internet is growing dressily day and night. One of the major problem in internet is to reduce the loss of packet during transmission. There are various nodes or devices so called router, switch, hub, and repeater are there between sender and receiver. Since the responsibility of network layer to transfer the packet to source to destination. Router is a network layer device, which route the data packets. Router give the path to the packets so that they reach the destination with minimum time and minimum loss. Each and every router has a buffer space in which packets wait for processing. This is known as queue of packets. These are also known as active queue, because they are alive they are waiting for processing they wait due to router processor speed, incoming packet rate, outgoing packet rates also due to difference of band width between incoming and outgoing packets. There are various active queue management mechanism or algorithm were developed such as RED, BLUE, SFB, CHOKE, PURPLE etc. but have their pros and cons. In this paper active queue management is done by using fuzzy logic. Basically fuzzy logic is used for decision making. Same here which packet have to drop or which not will be decided by fuzzy logic and some parameters which are used in this paper. There will be some membership graphs and rules and Mamdani mechanism use to get appropriate answer. Also a dataset is used to validate the theory.