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Integral sliding-mode robust observer-based congestion control for wireless access networks

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Journal of control and Decision 2022年第2期9卷 152-164页

作者： Ladan Khoshnevisan Farzad R.Salmasia Xinzhi Liub School of Electrical and Computer Engineering College of EngineeringUniversity of TehranTehranIran bDepartment of Applied Mathematics Faculty of MathematisUniversity of WaterlooWaterlooCanada

Designing a robust active queue management(RAQM)is mandatory to avoid congestion in networks with wireless access links,because transmission control protocol(TCP)can detect con-gestion after its occurrence in a communication network and wireless links suffer from bottleneck capacity variations caused by fading and packet error rate(PER)in the acknowledgement pack-ets.Furthermore,the average window size cannot be measured explicitly from the output signal and input and state delay are imposed to a network,which complicate theRAQMdesign problem in nonlinear models.So,the main contribution of this study is to design a robust observer based control procedure based on integral sliding mode protocol to estimate the average window size,to control congestion in a TCP/RAQM network and to compensate input and state delay.Sim-ulation results via professional simulator NS-2 and SIMULINK confirm that the procedure can effectively estimate the window size and can robustly avoid congestion.

关键词： congestion control integral sliding mode robust active queue management(RAQM) robust observer-based control(ROBC) transmission control protocol(TCP) wireless access network

Coupled CUBIC congestion control for MPTCP in Broadband Networks

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Computer Systems Science & Engineering 2023年第4期45卷 99-115页

作者： Jae Yong Lee Byung Chul Kim Youngmi Kwon Kimoon Han Department of Information and Communications Engineering Chungnam National UniversityDaejeon34134Korea Agency for Defense Development Daejeon34186Korea

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.

关键词： MPTCP congestion control Coupled CUBIC high BDP network

QoS-Aware congestion control with Online Learning

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China Communications 2023年第2期20卷 168-178页

作者： Lei Zhang Kewei Zhu Yong Cui Yong Jiang Zhongguancun Laboratory Beijing 100094China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

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 *** 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.

关键词： congestion control quality of service online learning

Plume:Lightweight and Generalized congestion control with Deep Reinforcement Learning

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China Communications 2022年第12期19卷 101-117页

作者： Dehui Wei Jiao Zhang Xuan Zhang Chengyuan Huang State Key Laboratory of Networking and Switching Technology BUPT 100876China

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.

关键词： congestion control deep reinforcement learning lightweight generalization

Intelligent DoS Attack Detection with congestion control Technique for VANETs

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Computers, Materials & Continua 2022年第7期72卷 141-156页

作者： R.Gopi Mahantesh Mathapati B.Prasad Sultan Ahmad Fahd N.Al-Wesabi Manal Abdullah Alohali Anwer Mustafa Hilal Department of Computer Science and Engineering Dhanalakshmi Srinivasan Engineering CollegePerambalur621212India Department of Computer Science and Engineering RajaRajeswari College of EngineeringBengaluru560074India Department of Information Technology Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Computer Science College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia&Faculty of Computer and ITSana’a UniversitySana’a15347Yemen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

VehicularAd hoc Network(VANET)has become an integral part of Intelligent Transportation Systems(ITS)in today’s *** is a network that can be heavily scaled up with a number of vehicles and road side units that keep fluctuating in real *** is susceptible to security issues,particularly DoS attacks,owing to maximum unpredictability in location.So,effective identification and the classification of attacks have become the major requirements for secure data transmission in VANET.At the same time,congestion control is also one of the key research problems in VANET which aims at minimizing the time expended on roads and calculating travel time as well as waiting time at intersections,for a traveler.With this motivation,the current research paper presents an intelligent DoS attack detection with congestion control(IDoS-CC)technique for VANET.The presented IDoSCC technique involves two-stage processes namely,Teaching and Learning Based Optimization(TLBO)-based congestion control(TLBO-CC)and Gated Recurrent Unit(GRU)-based DoS detection(GRU-DoSD).The goal of IDoS-CC technique is to reduce the level of congestion and detect the attacks that exist in the network.TLBO algorithm is also involved in IDoS-CC technique for optimization of the routes taken by vehicles via traffic signals and to minimize the congestion on a particular route instantaneously so as to assure minimal fuel utilization.TLBO is applied to avoid congestion on roadways.Besides,GRU-DoSD model is employed as a classification model to effectively discriminate the compromised and genuine vehicles in the network.The outcomes from a series of simulation analyses highlight the supremacy of the proposed IDoS-CC technique as it reduced the congestion and successfully identified the DoS attacks in network.

关键词： VANET intelligent transportation systems congestion control attack detection dos attack deep learning

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

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Journal of Systems Engineering and Electronics 2007年第1期18卷 101-110页

作者： Liu Zhixin Guan Xinping Inst. of Electrical Engineering Yanshan Univ. Qinhuangdao 066004 E R. China

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.

关键词： ATM networks congestion control control theory Tracing-queue QoS

congestion control method: improved ERICA algorithm based on available bandwidth prediction using neural networks

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Journal of Systems Engineering and Electronics 2005年第1期16卷 151-154页

作者： LiuZhixin GuanXinping LongChengnian InstituteofElectricalEngineering YanshanUniversityOinhuangdao066004P.R.China

The improved ERICA algorithm for ABR flow congestion control is presented based on available bandwidth prediction using the BP neural networks in ATM networks. The switch periodically calculates the available bandwidth, monitors the load of network and updates the ER value according to the PERICA algorithm. The proposed algorithm can keep better performance than ERICA algorithm in simulations.

关键词： congestion control BP neural network PERICA.

congestion control algorithm in large-delay uncertain networks

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控制理论与应用（英文版） 2007年第1期5卷 67-70页

作者： Fengjie YIN Yuanwei JING Yuanjiu GONG School of Information Science and Technology Liaoning University Shenyang Liaoning 110036 China School of Information Science and Engineering Northeastern University Shenyang Liaoning 110004 China

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.

关键词： congestion control Large delay Active queue management Smith predictor Fuzzy logic control

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

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Journal of Systems Engineering and Electronics 2008年第6期19卷 1208-1214页

作者： Sun Wei Tian Naishuo Li Shiyong Guan Xinping Coll. of Information Science and Engineering Yanshan Univ. Qinhuangdao 066004 P. R. China Coll. of Science Yanshan Univ. Qinhuangdao 066004 P. R. China School of Electronics and Information Engineering Beijing Jiaotong Univ. Beijing 100044 P. R. China Inst. of Electrical Engineering Yanshan Univ. Qinhuangdao 066004 P. R. China

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.

关键词： congestion control random loss delay convergence stability Nyquist criterion.