Adaptive Congestion Control Algorithm Research Articles

Congestion tracking control of multi-bottleneck TCP networks with input-saturation and dead-zone

<abstract><p>This paper discusses the congestion control challenges in a network employing multi-bottleneck Transmission Control Protocol/Active Queue Management (TCP/AQM). The study specifically focuses on networks characterized by input nonlinearity and unknown disturbances. We regard the network as a whole, and consider the influence between multiple nodes and unknown disturbance, a dynamic model of multi-bottleneck network is established. And the impact of dead zone and saturation on the system is taken into account for the first time in the model, the builded TCP/AQM model is more practicable. Based on the characteristics of fuzzy logic systems (FLS), combined with backstepping technology and Lyapunov function, an adaptive congestion control algorithm is designed to make full use of the link resources of each node and improve the network utilization. Ultimately, the proposed algorithm's efficacy and superiority are substantiated through simulation.</p></abstract>

An adaptive congestion control algorithm

The congestion of the network increases exponentially due to continuous growth of the Internet. TCP is a protocol of Transport layer which deals with the congestion of the network. TCP has many variants to deal with different types of congestion problems. Congestion of the network depends on many factors like transfer of packet size, type of cross traffic, number of competing connections,the load on every link in the path, router buffer size and bottleneck queue size. This paper presents a new congestion detection method which is based on bottleneck queue size. It is estimated according to variation of round-trip time. The experimental results confirm that the proposed TCP provide better results for throughput and packet drops.

Generalized TCP-RED dynamical model for Internet congestion control

Abstract Adaptive management of traffic congestion in the Internet is a complex problem that can gain useful insights from a dynamical approach. In this paper we propose and analyze a one-dimensional, discrete-time nonlinear model for Internet congestion control at the routers. Specifically, the states correspond to the average queue sizes of the incoming data packets and the dynamical core consists of a monotone or unimodal mapping with a unique fixed point. This model generalizes a previous one in that additional control parameters are introduced via the data packet drop probability with the objective of enhancing stability. To make the analysis more challenging, the original model was shown to exhibit the usual features of low-dimensional chaos with respect to several system and control parameters, e.g., positive Lyapunov exponents and Feigenbaum-like bifurcation diagrams. We concentrate first on the theoretical aspects that may promote the unique stationary state of the system to a global attractor, which in our case amounts to global stability. In a second step, those theoretical results are translated into stability domains for robust setting of the new control parameters in practical applications. Numerical simulations confirm that the new parameters make it possible to extend the stability domains, in comparison with previous results. Therefore, the present work may lead to an adaptive congestion control algorithm with a more stable performance than other algorithms currently in use.

A novel solution for real‐time wireless networks: Telehealth psychological services in rural area

AbstractTelehealth psychological services is a time‐efficient and cost‐effective therapy solution for persons in rural areas. The high congestion resulting from these infrastructure issues, which includes low‐bandwidth wireless connections and channels prone to data loss, tends to increase video delays, thereby making real‐time video transmission during telehealth psychological services challenging. The purpose of this study is, hence, to enable the successful implementation of telehealth psychological services in rural areas by minimising end‐to‐end video transmission delay and improving bandwidth efficiency. Our proposed system uses a distortion‐aware TCP‐friendly adaptive congestion control algorithm that adapts the congestion window size according to path characteristics and quality. Indeed, evaluation results show that our algorithm—as compared to a reference—significantly improves peak signal‐to‐noise ratio and end‐to‐end delay; thus, suggesting that the adoption of an adaptive congestion window size in our system can improve network bandwidth efficiency and reduce information delay resulting from packet queuing and unnecessary packet loss. The outcome is successful high‐definition video transmission during telehealth psychological services.

An Adaptive Solution for Congestion Control in CoAP-based Group Communications

The use of lightweight devices and constrained resources like Wireless Sensors Network (WSN) makes patterns traffic in the Internet of Things (IoT) different from the ones in conventional networks. One of the most emerging messaging protocols used to address the needs of these lightweight IoT nodes is Constrained Application Protocol (CoAP). CoAP presents a lot of advantages compared to other IoT application layer protocols; it ensures group communication via multicast communications between a server and multiple clients. Nevertheless, it doesn’t support a group communication from a client to multiple servers; it relies on multiple unicasts to do so. Regarding the fact that these constrained devices communicate via a large amount of messages and notifications, network congestion occurs. This paper proposes an adaptive congestion control algorithm designed for group communications using unicast between a client and multiple servers. Simulated results show that the proposed mechanism can appropriately achieve higher performances in terms of response time and packet loss.

D-ACB: Adaptive Congestion Control Algorithm for Bursty M2M Traffic in LTE Networks

When incorporating machine-to-machine (M2M) communications into the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) networks, one of the challenges is the traffic overload since many machine-type communication (MTC) devices activated in a short period of time may require access to an evolved node B (eNodeB) simultaneously. One approach to tackle this problem is by using an access class barring (ACB) mechanism with an ACB factor to defer some activated MTC devices transmitting their access requests. In this paper, we first present an analytical model to determine the expected total service time, i.e., the time used by all MTC devices to successfully access the eNodeB. In the ideal case that the eNodeB is aware of the number of backlogged MTC devices, we determine the optimal value of the ACB factor to reduce traffic overload. To better utilize the random access resources shared among human users and MTC devices in LTE networks, we propose to dynamically allocate a number of random access preambles for MTC devices. We further propose two dynamic ACB (D-ACB) algorithms for fixed and dynamic preamble allocation schemes to determine the ACB factors without a priori knowledge of the system backlog. Simulation results show that the proposed D-ACB algorithms achieve almost the same performance as the optimal performance obtained in the ideal case. The proposed D-ACB for dynamic preamble allocation algorithm can reduce both the total time to serve all MTC devices and the average number of random access opportunities required by each MTC device.

CLTCP: An Adaptive TCP Congestion Control Algorithm Based on Congestion Level

The Transmission Control Protocol (TCP) has been profusely used by diverse applications such as FTP, email, and HTTP. In recent decades, numerous TCP variants have been developed to fit the fast increasing of network capacities and improve the performance of TCP algorithms in various scenarios, particularly in the high-bandwidth-delay-product (high-BDP) and lossy networks. Although the performance improvements are different for different TCP under different networking conditions, implementing a new congestion control algorithm that is suitable for a wide range of network conditions is still a challenge. In this letter, we propose a novel scheme, i.e., the congestion-level-based TCP (CLTCP), which could perform effectively in both high-BDP and lossy networks. Different from the TCP-FIT, the CLTCP does not use the delay variation but the congestion level as a signal to control the number of virtual parallel flows in a TCP connection. This could avoid the influence of the delay measurement error in the TCP-FIT. Extensive experiments in NS-2 show that the performance of the CLTCP is significantly improved, as compared to other state-of-the-art algorithms, while maintaining good fairness.

Adaptive Logarithmic Increase Congestion Control Algorithm for Satellite Networks

This paper presents a new algorithm called the adaptive logarithmic increase and adaptive decrease algorithm (A-LIAD), which mainly addresses the Round-Trip Time (RTT) fairness problem in satellite networks with a very high propagation delay as an alternative to the current TCP congestion control algorithm. We defined a new increasing function in the fashion of a logarithm depending on the increasing factor α, which is different from the other logarithmic increase algorithm adopting a fixed value of α = 2 leading to a binary increase. In A-LIAD, the α value is derived in the RTT function through the analysis. With the modification of the increasing function applied for the congestion avoidance phase, a hybrid scheme is also presented for the slow start phase. From this hybrid scheme, we can avoid an overshooting problem during a slow start phase even without a SACK option. To verify the feasibility of the algorithm for deployment in a high-speed and long-distance network, several aspects are evaluated through an NS-2 simulation. We performed simulations for intra- and inter-fairness as well as utilization in different conditions of varying RTT, bandwidth, and PER. From these simulations, we showed that although A-LIAD is not the best in all aspects, it provides a competitive performance in almost all aspects, especially in the start-up and packet loss impact, and thus can be an alternative TCP congestion control algorithm for high BDP networks including a satellite network.

Study on the Adaptive Congestion Control Algorithms for Wireless Sensor Networks

As the study on and promotion of wireless sensor networks (WSN) are deepening, people have increasingly higher requirements for the transmission speed and transmission performance of wireless sensor networks. Network congestion is an important factor of the transmission performance of a network, so congestion control becomes a hot research topic in the studies on the improvement of WSN services. Based on the study on WSN congestion control mechanism, this paper proposes an adaptive congestion control algorithm and simulates the algorithm. The simulation result shows that this algorithm can ensure stable network performance.

Adaptive Congestion Control via Dynamic Output Feedback

This paper presents an adaptive congestion control algorithm for Internet with time-varying uncertainties. The controller is designed via dynamic output feedback. Simulation result shows that the proposed algorithm has good performance.

TCP-Adaptive in High Speed Long Distance Networks

With the development of high performance computing and increasing of network bandwidth, more and more applications require fast data transfer over high-speed long-distance networks. Research shows that the standard TCP Reno cannot fulfill the requirement of fast transfer of massive data due to its conservative congestion control mechanism. Some works have been proposed to improve the TCP throughput performance using more aggressive window increasing tactics and obtain substantial achievements. However, they cannot be strictly proved to be comprehensively suitable for high-speed complex network environments. In this paper, we propose TCP-Adaptive, an adaptive congestion control algorithm adjusting the increasing congestion window dynamically. The algorithm improves logarithmic detection procedure for available bandwidth in the flow path by distinguishing the first detection in congestion avoidance and retransmission timeout. On the other hand, an adaptive control algorithm is proposed to achieve better performance in high-speed long-distance networks. The algorithm uses round trip time (RTT) variations to predict the congestion trends to update the increments of congestion window. Simulations verify the property of TCP-Adaptive and show satisfying performance in throughput, RTT fairness aspects over high-speed long-distance networks. Especially in sporadic loss environment, TCP-Adaptive shows a significant adaptability with the variations of link quality

LIMERIC: A Linear Adaptive Message Rate Algorithm for DSRC Congestion Control

Wireless vehicle-to-vehicle (V2V) and vehicle-toinfrastructure (V2I) communication holds great promise for significantly reducing the human and financial costs of vehicle collisions. A common characteristic of this communication is the broadcast of a device's core state information at regular intervals (e.g., vehicle speed and location or traffic signal state and timing). Unless controlled, the aggregate of these broadcasts will congest the channel under dense traffic scenarios, reducing the effectiveness of collision avoidance applications that use transmitted information. Active congestion control using distributed techniques is a topic of great interest for establishing the scalability of this technology. This paper defines a new adaptive congestion control algorithm that can be applied to the message rate of devices in this vehicular environment. While other published approaches rely on binary control, the LInear MEssage Rate Integrated Control (LIMERIC) algorithm takes advantage of full-precision control inputs that are available on the wireless channel. The result is provable convergence to fair and efficient channel utilization in the deterministic environment, under simple criteria for setting adaptive parameters. This “perfect” convergence avoids the limit cycle behavior that is inherent to binary control. We also discuss several practical aspects associated with implementing LIMERIC, including guidelines for the choice of system parameters to obtain desired utilization outcomes, a gain saturation technique that maintains robust convergence under all conditions, convergence with asynchronous updates, and using channel load to determine the aggregate message rate that is observable at a receiver. This paper also extends the convergence analysis for two important cases, i.e., measurement noise in the input signal and delay in the update process. This paper illustrates key analytical results using MATLAB numerical results and employs standard NS-2 simulations to demonstrate the performance of LIMERIC in several high-density scenarios.

Adaptive Congestion Control Protocol (ACCP) for Wireless Sensor Networks

In Wireless Sensor Networks (WSN) when an event is detected there is an increase in data traffic that might lead to packets being transmitted through the network close to the packet handling capacity of the WSN. The WSN experiences a decrease in network performance due to packet loss, long delays, and reduction in throughput. In this paper we developed an adaptive congestion control algorithm that monitors network utilization and adjust traffic levels and/or increases network resources to improve throughput and conserve energy. The traffic congestion control protocol DelStatic is developed by introducing backpressure mechanism into NOAH. We analyzed various routing protocols and established that DSR has a higher resource congestion control capability. The proposed protocol, ACCP uses a sink switching algorithm to trigger DelStatic or DSR feedback to a congested node based on its Node Rank. From the simulation results, ACCP protocol does not only improve throughput but also conserves energy which is critical to sensor application survivability on the field. Our Adaptive Congestion control achieved reliability, high throughput and energy efficiency.

Robust decentralized adaptive nonquadratic congestion control algorithm for a class of delayed networks

Due to the recent advances in communication networks, congestion control can be considered as of paramount importance and has spurred a significant amount of research. In this paper, the problem of congestion control in the presence of channel uncertainty is addressed in wireless sensor networks (WSNs). Since WSNs are normally set up in adverse conditions, robustness against environmental strains and also the ability to autonomously recover from error situations is mostly demanded. Based on nonlinear dynamics point of view, it is essential to consider delay in the analysis of general congestion control schemes. This paper presents a novel, robust decentralized adaptive nonquadratic congestion control scheme (RDANQCC), which is robust to queue length changes and the consequent delay changes. RDANQCC includes an adaptive back-off interval selection that works in concert with a robust controller. Using queue utilization and channel estimation algorithm, congestion can be detected and a suitable rate is enforced by adaptive back-off interval selection. An iterative linear matrix inequality (ILMI) is utilized to solve our control problem. Unlike previous schemes, varying desired queue length is considered in this paper and two cases are proposed for fixed and varying desired queue length and it is shown that in the latter our controller renders better performance compared with the former. The convergence analysis of RDANQCC is demonstrated by the use of nonquadratic Lyapunov-based approach. Extended simulation results demonstrate that RDANQCC renders better performance in comparison with other schemes available in the literature.

QTCP: Improving Throughput Performance Evaluation with High-Speed Networks

High-speed TCP (HSTCP) is one of the several popular variants of TCP aimed at the optimization of TCP for high-speed networks. Like all other variants, HSTCP also fails to take full shared bandwidth utilization and offers low throughput rate, high packet loss rate and poor fairness. To overcome these problems, a new adaptive congestion control algorithm with high-speed delay product network named, the Quick Transport Control Protocol (QTCP) has been designed through this research. The basic idea of QTCP has been inspired by the HSTCP and CUBIC, which supported to enhance the algorithm. Three main component of QTCP window control algorithm are α phase, β phase and multiplicative decrease. An experimental setup was designed for the evaluation of QTCP. In this experiment, the QTCP was evaluated based on average throughput and fairness between multiple flows with the same RTT. QTCP performs tuning of the sender side modification based on slow start and AIMD algorithms of HSTCP and CUBIC. QTCP provides higher throughput and enhanced fairness as compared to most of the currently available TCP variants for high-speed networks. The improved throughput and fairness remains intact even in the presence of background traffic. NS-2 simulator-based results with different configurations are presented, discussed in detail, and evaluated with other popular algorithms.

Adaptive Congestion Controller for ABR Traffic in ATM Network

One of the imperatives for improving the quality-of-service (QoS) of high-speed networks of next generation is to reduce congestion. Congestion occurs when the resource demand exceeds the capacity of the network. The purpose of this paper is to analyze the performance of Robust Adaptive Congestion Control algorithm for available bit rate traffic in asynchronous transfer mode networks and suggest improvements of the algorithm for better performance and fairness. The results of simulation presented here corroborates the fact that the improved algorithm reduces settling time and cell loss ratio and thus maximizes utilization of the network.

Global asymptotic stability of internet adaptive congestion control algorithm

To ensure the quality of service of the network, the internet applies network congestion control algorithms to adjust the rate to improve the serving capacity. Based on the working mechanisms of internet communication systems, a dynamic internet congestion control primal dual algorithm is presented. By applying the Lyapunov stability theorem, the global asymptotic stability of the dynamic algorithm with negligible communication delays is studied. Furthermore, the global asymptotic stability of the dynamic algorithm with communication delays is analysed by means of the Lyapunov-Krasovskii theorem. Finally, computer simulations show the validity of these results.

Effort/gains dynamics in heterogeneous networks

AbstractWe investigate the behaviour of TCP(α, β) protocols in the presence of wireless networks. We seek an answer to strategic issues of maximizing energy and bandwidth exploitation, without damaging the dynamics of multiple‐flow equilibrium. We take a fresh perspective on protocol design: What is the return of the effort that a protocol expends? Can we achieve more gains with less effort? We study first the design assumptions of TCP(α, β) protocols and discuss the impact of equation‐based modulation of α and β on protocol efficiency. We introduce two new measures to capture protocol behaviour: the ‘Extra Energy Expenditure’ and the ‘Unexploited Available Resource Index’. We confirm experimentally that, in general, smoothness and responsiveness constitute a tradeoff; however, we show that this tradeoff does not graft its dynamics into a conservative/aggressive behaviour, as it is traditionally believed. We uncover patterns of unjustified tactics; our results suggest that an adaptive congestion control algorithm is needed to integrate the dynamics of heterogeneous networks into protocol behaviour. Copyright © 2007 John Wiley & Sons, Ltd.

An Efficient Designed Robust Adaptive Congestion Controller for ABR Traffic in ATM Network

In the computer networks, congestion occurs when the resource demands exceeds the capacity, which the network can provide. The presence of too many packets in the network, which the network is not able to cope with due to its limited resources and it begins losing packets, gives birth to the situation called congestion.The aims of this paper is to analyze the performance of Robust Adaptive Congestion Control algorithm for ABR traffic in ATM networks and modify this algorithm for better performance. The main goal of ABR traffic control is to provide fairness among all the VCs with a minimal cell loss ratio and maximum utilization of the network.