End-to-end rate-based congestion control with random loss:convergence and stability

The convergence and stability analysis for two end-to-end rate-based congestion control algorithms with unavoidable random loss in packets are presented, which can be caused by, for example, errors on wireless links. The convergence rates of these two algorithms are analyzed by linearizing them around their equilibrium points, since they are globally stable and can converge to their unique equilibrium points. Some sufficient conditions for local stability in the presence of round-trip delay are obtained based on the general Nyquist criterion of stability. The stability conditions can be considered to be more general. If random loss in the first congestion control algorithm is not considered, they reduce to the local stability conditions which have been obtained in some literatures. Furthermore, sufficient conditions for local stability of a new congestion control algorithm have also been obtained if random loss is not considered in the second congestion control algorithm.

Congestion Control Algorithms for the Internet-A Secondary Publication

In the last five years,there has been a V-shaped recovery in the number of papers on congestion control algorithms on the Internet.In this paper,congestion problems on the Internet are discussed,such as congestion collapse and bufferbloat from the perspective of the necessity of congestion control algorithms.The typical congestion control algorithms are introduced,and the research areas and methods of congestion control algorithms are described.Recent research trends and future prospects of congestion control algorithms are also presented.

QoS-Aware Congestion Control with Online Learning

In emerging applications such as industrial control and autonomous driving,end-to-end deterministic quality of service(QoS)transmission guarantee has become an urgent problem to be solved.Internet congestion control algorithms are essential to the performance of applications.However,existing congestion control schemes follow the best-effort principle of data transmission without the perception of application QoS requirements.To enable data delivery within application QoS constraints,we leverage an online learning mechanism to design Crimson,a novel congestion control algorithm in which each sender continuously observes the gap between current performance and pre-defined QoS.Crimson can change rates adaptively that satisfy application QoS requirements as a result.Across many emulation environments and real-world experiments,our proposed scheme can efficiently balance the different trade-offs between throughput,delay and loss rate.Crimson also achieves consistent performance over a wide range of QoS constraints under diverse network scenarios.

Coupled CUBIC Congestion Control for MPTCP in Broadband Networks

Recently,multipath transmission control protocol(MPTCP)was standardized so that data can be transmitted through multiple paths to utilize all available path bandwidths.However,when high-speed long-distance networks are included in MPTCP paths,the traffic transmission performance of MPTCP is severely deteriorated,especially in case the multiple paths’characteristics are heavily asymmetric.In order to alleviate this problem,we propose a“Coupled CUBIC congestion control”that adopts TCP CUBIC on a large bandwidth-delay product(BDP)path in a linked increase manner for maintaining fairness with an ordinary TCP traversing the same bottleneck path.To verify the performance excellence of the proposed algorithm,we implemented the Coupled CUBIC Congestion Control into Linux kernels by modifying the legacy MPTCP linked-increases algorithm(LIA)congestion control source code.We constructed asymmetric heterogeneous network testbeds mixed with large and small BDP paths and compared the performances of LIA and Coupled CUBIC by experiments.Experimental results show that the proposed Coupled CUBIC utilizes almost over 80%of the bandwidth resource in the high BDP path,while the LIA utilizes only less than 20%of the bandwidth for the same path.It was confirmed that the resource utilization and traffic transmission performance have been greatly improved by using the proposed Coupled CUBIC in high-speed multipath networks,as well as maintaining MPTCP fairness with competing single-path CUBIC or Reno TCP flows.

Congestion Control Using In-Network Telemetry for Lossless Datacenters

In the Ethernet lossless Data Center Networks (DCNs) deployedwith Priority-based Flow Control (PFC), the head-of-line blocking problemis still difficult to prevent due to PFC triggering under burst trafficscenarios even with the existing congestion control solutions. To addressthe head-of-line blocking problem of PFC, we propose a new congestioncontrol mechanism. The key point of Congestion Control Using In-NetworkTelemetry for Lossless Datacenters (ICC) is to use In-Network Telemetry(INT) technology to obtain comprehensive congestion information, which isthen fed back to the sender to adjust the sending rate timely and accurately.It is possible to control congestion in time, converge to the target rate quickly,and maintain a near-zero queue length at the switch when using ICC. Weconducted Network Simulator-3 (NS-3) simulation experiments to test theICC’s performance. When compared to Congestion Control for Large-ScaleRDMA Deployments (DCQCN), TIMELY: RTT-based Congestion Controlfor the Datacenter (TIMELY), and Re-architecting Congestion Managementin Lossless Ethernet (PCN), ICC effectively reduces PFC pause messages andFlow Completion Time (FCT) by 47%, 56%, 34%, and 15.3×, 14.8×, and11.2×, respectively.

Local Bifurcation Analysis of a Delayed Fractional-order Dynamic Model of Dual Congestion Control Algorithms

In this paper, we propose a delayed fractional-order congestion control model which is more accurate than the original integer-order model when depicting the dual congestion control algorithms. The presence of fractional orders requires the use of suitable criteria which usually make the analytical work so harder. Based on the stability theorems on delayed fractionalorder differential equations, we study the issue of the stability and bifurcations for such a model by choosing the communication delay as the bifurcation parameter. By analyzing the associated characteristic equation, some explicit conditions for the local stability of the equilibrium are given for the delayed fractionalorder model of congestion control algorithms. Moreover, the Hopf bifurcation conditions for general delayed fractional-order systems are proposed. The existence of Hopf bifurcations at the equilibrium is established. The critical values of the delay are identified, where the Hopf bifurcations occur and a family of oscillations bifurcate from the equilibrium. Same as the delay,the fractional order normally plays an important role in the dynamics of delayed fractional-order systems. It is found that the critical value of Hopf bifurcations is crucially dependent on the fractional order. Finally, numerical simulations are carried out to illustrate the main results.

Connect & Drive:design and evaluation of cooperative adaptive cruise control for congestion reduction

Road throughput can be increased by driving at small inter-vehicle time gaps. The amplification of velocity disturbances in upstream direction, however, poses limitations to the minimum feasible time gap. This effect is covered by the notion of string stability. String-stable behavior is thus considered an essential requirement for the design of automatic distance control systems, which are needed to allow for safe driving at time gaps well below 1 s. Using wireless inter-vehicle communications to provide real-time information of the preceding vehicle, in addition to the information obtained by common Adaptive Cruise Control （ACC） sensors, appears to significantly decrease the feasible time gap, which is shown by practical experiments with a test fleet consisting of six passenger vehicles. The large-scale deployment of this system, known as Cooperative ACC （CACC）, however, poses challenges with respect to the reliability of the wireless communication system. A solution for this scalability problem can be found in decreasing the transmission power and/or beaconing rate, or adapting the communications protocol. Although the main CACC objective is to increase road throughput, the first commercial application of CACC is foreseen to be in truck platooning, since short distance following is expected to yield significant fuel savings in this case.

Bifurcation and stability of an improved time-delayed fluid flow model in internet congestion control

Based on the fluid flow time-delayed model proposed by Misra et al in internet congestion control, one modified time-delayed model is presented, where the influence of the communication delay on the router queue length is investigated in detail. The main advantage of the new model is that its stability domain is larger even without an extra controller. By linear stability analysis and numerical simulation, tbe effectiveness and feasibility of the novel model in internet congestion control are verified.

Hybrid control of bifurcation and chaos in stroboscopic model of Internet congestion control system

Interaction between transmission control protocol （TCP） and random early detection （RED） gateway in the Internet congestion control system has been modelled as a discrete-time dynamic system which exhibits complex bifurcating and chaotic behaviours. In this paper, a hybrid control strategy using both state feedback and parameter perturbation is employed to control the bifurcation and stabilize the chaotic orbits embedded in this discrete-time dynamic system of TCP/RED. Theoretical analysis and numerical simulations show that the bifurcation is delayed and the chaotic orbits are stabilized to a fixed point, which reliably achieves a stable average queue size in an extended range of parameters and even completely eliminates the chaotic behaviour in a particular range of parameters. Therefore it is possible to decrease the sensitivity of RED to parameters. By using the hybrid strategy, we may improve the stability and performance of TCP/RED congestion control system significantly.

Bursting-like motion induced by time-varying delay in an internet congestion control model

Time delay is an problem of intemet congestion important parameter in the control. According to some researches, time delay is not always constant and can be viewed as a periodic function of time for some cases. In this work, an internet congestion control model is consid- ered to study the time-varying delay induced bursting-like motion, which consists of a rapid oscillation burst and quies- cent steady state. Then, for the system with periodic delay of small amplitude and low frequency, the method of multiple scales is employed to obtain the amplitude of the oscillation. Based on the expression of the asymptotic solution, it can be found that the relative length of the steady state increases with amplitude of the variation of time delay and decreases with frequency of the variation of time delay. Finally, an effective method to control the bursting-like motion is pro- posed by introducing a periodic gain parameter with appropriate amplitude. Theoretical results are in agreement with that from numerical method.

Congestion control scheme in ATM networks based on fast tracing-queue

One of the more challenging and unresolved issues in ATM networks is the congestion control of available bit rate （ABR）. The dynamic controller is designed based on the control theory and the feedback mechanism of explicit rates With the given method of a chosen parameter, it can guarantee the stability of the controller and closed loop system with propagation delay and bandwidth oscillation. It needs less parameters（only one） to be designed. The queue length can converge to the given value in the least steps. The fairness of different connections is considered further. The simulations show better performance and good quality of service（QoS） is achieved.

Suppression of oscillatory congestion via trunk link bandwidth and control gain in star network

The time delay-induced instability in an Internet congestion control model is investigated. The star topology is considered, and the link bandwidth ratio and the control gain are selected as the tunable parameters for congestion suppression. The stability switch boundary is obtained by the eigenvalue analysis for the linearized system around the equilibrium. To investigate the oscillatory congestion when the equilibrium becomes unstable, the center manifold reduction and the normal form theory are used to study the periodic oscillation induced by the delay. The theoretical analysis and numerical simulation show that the ratio between bandwidths of the trunk link and the regular link,rather than these bandwidths themselves, is crucial for the stability of the congestion control system. The present results demonstrate that it is not always effective to increase the link bandwidth ratio for stabilizing the system, and for some certain delays, adjusting the control gain is more efficient.

Congestion control algorithm in large-delay uncertain networks

Based on Smith-fuzzy controller, a new active queue management （AQM） algorithm adaptable to the large-delay uncertain networks is presented. It can compensate the negative impact on the queue stability caused by the large delay, and it also maintains strong robustness under the condition of dynamic network fluid. Its stability is proven through Lyapunov method. Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small, the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and, in particular, the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.

Plume:Lightweight and Generalized Congestion Control with Deep Reinforcement Learning

Congestion control(CC)is always an important issue in the field of networking,and the enthusiasm for its research has never diminished in both academia and industry.In current years,due to the rapid development of machine learning(ML),the combination of reinforcement learning(RL)and CC has a striking effect.However,These complicated schemes lack generalization and are too heavyweight in storage and computing to be directly implemented in mobile devices.In order to address these problems,we propose Plume,a high-performance,lightweight and generalized RL-CC scheme.Plume proposes a lightweight framework to reduce the overheads while preserving the original performance.Besides,Plume innovatively modifies the framework parameters of the reward function during the retraining process,so that the algorithm can be applied to a variety of scenarios.Evaluation results show that Plume can retain almost all the performance of the original model but the size and decision latency can be reduced by more than 50%and 20%,respectively.Moreover,Plume has better performances in some special scenes.

A Routing Protocol for Wireless Sensor Networks with Congestion Control

This paper proposed a novel RED protocol which takes the node’s energy into account depending on the length of the data packet. It also proposed a routing protocol for wireless sensor networks with congestion control which imitates the ant colony foraging behavior. Sensor nodes choose routings according to the pheromone density. The experiment result shows that the algorithm balances the energy consumption of each node. It mitigated congestion effectively with the proposed routing protocol.

Optimal congestion control algorithm for ad hoc networks: Penalty function-based approach

In this paper, based on the inherent characteristic of the contention relation between flows in ad hoc networks, we introduce the notion of the link’s interference set, extend the utility maximization problem representing congestion control in wireline networks to ad hoc networks, apply the penalty function approach and the subgradient method to solve this problem, and propose the congestion control algorithm Penalty function-based Optical Congestion Control (POCC) which is implemented in NS2 simulator. Specifically, each link transmits periodically the information on its congestion state to its interference set; the session at each source adjusts the transmission rate based on the optimal tradeoff between the utility value and the congestion level which the interference set of the links that this session goes though suffers from. MATLAB-based simulation results showed that POCC can approach the globally optimal solution. The NS2-based simulation results showed that POCC outperforms default TCP and ATCP to achieve efficient and fair resource allocation in ad hoc networks.

Streaming and congestion control using scalable video coding based on H.264/AVC

This paper presents a streaming system using scalable video coding based on H.264/AVC. The system provides a congestion control algorithm supported by channel bandwidth estimation of the client. It uses retransmission only for packets of the base layer to disburden the congested network. The bandwidth estimation allows for adjusting the transmission rate quickly to the current available bandwidth of the network. Compared to binomial congestion control, the proposed system allows for shorter start-up times and data rate adaptation. The paper describes the components of this streaming system and the results of experiments showing that the proposed approach works effectively for streaming video.

Quality incentive based congestion control for multimedia communication over IP networks

In this paper we introduce a framework for using quality as an incentive to promote proper application level congestion control. Through integrating a joint-source channel coder and feedback-based congestion control scheme, we are able to construct accurate and efficient quality incentives. The framework is applicable in all network architectures where end-to-end congestion control may be used, and is as such not specific to either best-effort or traffic class-based architectures. The concept is presented along with preliminary simulations that highlight the resulting rate control accuracy. We also discuss how to implement some well-known congestion control schemes within our framework.

Improved Bat Algorithm Based Energy Efficient Congestion Control Scheme for Wireless Sensor Networks

Energy conservation and congestion control are widely researched topics in Wireless Sensor Networks in recent years. The main objective is to develop a model to find the optimized path on the basis of distance between source and destination and the residual energy of the node. This paper shows an implementation of nature inspired improved Bat Algorithm to control congestion in Wireless Sensor Networks at transport layer. The Algorithm has been applied on the fitness function to obtain an optimum solution. Simulation results have shown improvement in parameters like network lifetime and throughput as compared with CODA (Congestion Detection and Avoidance), PSO (Particle Swarm Optimization) algorithm and ACO (Ant Colony Optimization).

Analysis and Improvement of TCP Congestion Control Mechanism Based on Global Optimization Model

Network flow control is formulated as a global optimization problem of user profit. A general global optimization flow control model is established. This model combined with the stochastic model of TCP is used to study the global rate allocation characteristic of TCP. Analysis shows when active queue management is used in network TCP rates tend to be allocated to maximize the aggregate of a user utility functionU s (called,U s fairness). The TCP throughput formula is derived An improved TCP congestion control mechanism is proposed. Simulations show its throughput is TCP friendly when competing with existing TCP and its rate change is smoother. Therefore, it is suitable to carry multimedia applications.