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.

Venous Doppler flow patterns,venous congestion,heart disease and renal dysfunction:A complex liaison

The World Journal of Cardiology published an article written by Kuwahara et al that we take the pleasure to comment on.We focused our attention on venous congestion.In intensive care settings,it is now widely accepted that venous congestion is an important clinical feature worthy of investigation.Evaluating venous Doppler profile abnormalities at multiple sites could suggest adequate treatment and monitor its efficacy.Renal dysfunction could trigger or worsen fluid overload in heart disease,and cardio-renal syndrome is a well-characterized spectrum of disorders describing the complex interactions between heart and kidney diseases.Fluid overload and venous congestion,including renal venous hypertension,are major determinants of acute and chronic renal dysfunction arising in heart disease.Organ congestion from venous hypertension could be involved in the development of organ injury in several clinical situations,such as critical diseases,congestive heart failure,and chronic kidney disease.Ultrasonography and abnormal Doppler flow patterns diagnose clinically significant systemic venous congestion.Cardiologists and nephrologists might use this valuable,noninvasive,bedside diagnostic tool to establish fluid status and guide clinical choices.

An Adaptive Congestion Control Optimization Strategy in SDN-Based Data Centers

The traffic within data centers exhibits bursts and unpredictable patterns.This rapid growth in network traffic has two consequences:it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load.Consequently,persistent overload situations eventually result in network congestion.The Software Defined Network(SDN)technology is employed in data centers as a network architecture to enhance performance.This paper introduces an adaptive congestion control strategy,named DA-DCTCP,for SDN-based Data Centers.It incorporates Explicit Congestion Notification(ECN)and Round-Trip Time(RTT)to establish congestion awareness and an ECN marking model.To mitigate incorrect congestion caused by abrupt flows,an appropriate ECN marking is selected based on the queue length and its growth slope,and the congestion window(CWND)is adjusted by calculating RTT.Simultaneously,the marking threshold for queue length is continuously adapted using the current queue length of the switch as a parameter to accommodate changes in data centers.The evaluation conducted through Mininet simulations demonstrates that DA-DCTCP yields advantages in terms of throughput,flow completion time(FCT),latency,and resistance against packet loss.These benefits contribute to reducing data center congestion,enhancing the stability of data transmission,and improving throughput.

Ultrasound unveiling:Decoding venous congestion in heart failure for precision management of fluid status

This editorial discusses the manuscript by Di Maria et al,published in the recent issue of the World Journal of Cardiology.We here focus on the still elusive pathophysiological mechanisms underlying cardio-renal syndrome(CRS),despite its high prevalence and the substantial worsening of both kidney function and heart failure.While the measure of right atrial pressure through right cardiac catheterization remains the most accurate albeit invasive and costly procedure,integrating bedside ultrasound into diagnostic protocols may substantially enhance the staging of venous congestion and guide therapeutic decisions.In particular,with the assessment of Doppler patterns across multiple venous districts,the Venous Excess Ultrasound(VExUS)score improves the management of fluid overload and provides insight into the underlying factors contributing to cardio-renal interactions.Integrating specific echocardiographic parameters,particularly those concerning the right heart,may thus improve the VExUS score sensitivity,offering perspective into the nuanced comprehension of cardio-renal dynamics.A multidisciplinary approach that consistently incorporates the use of ultrasound is emerging as a promising advance in the understanding and management of CRS.

Portal vein pulsatility:An important sonographic tool assessment of systemic congestion for critical ill patients

In this editorial we comment on the article by Kuwahara et al,published in the recent issue of the World Journal of Cardiology.In this interesting paper,the authors showed a correlation between portal vein pulsatility ratio,examined by bedside ultrasonography,and prognosis of hospitalized patients with acute heart failure.Systemic congestion is being notoriously underdetected in the acutely ill population with conventional methods like clinical examination,biomarkers,central venous pressure estimation and X-rays.However,congestion should be a key therapeutic target due to its deleterious effects to end organ function and subsequently patient prognosis.Doppler flow assessment of the abdominal veins is gaining popularity worldwide,as a valuable tool in estimating comprehensively congestion and giving a further insight into hemodynamics and patient management.

An Effective Optimization Algorithm for Ant Colony Vehicular Congestion Management

Adaptability and dynamicity are special properties of social insects derived from the decentralized behavior of the insects. Authors have come up with designs for software solution that can regulate traffic congestion in a network transportation environment. The effectiveness of various researches on traffic management has been verified through appropriate metrics. Most of the traffic management systems are centered on using sensors, visual monitoring and neural networks to check for available parking space with the aim of informing drivers beforehand to prevent traffic congestion. There has been limited research on solving ongoing traffic congestion in congestion prone areas like car park with any of the common methods mentioned. This study focus however is on a motor park, as a highly congested area when it comes to traffic. The car park has two entrance gate and three exit gates which is divided into three Isle of parking lot where cars can park. An ant colony optimization algorithm (ACO) was developed as an effective management system for controlling navigation and vehicular traffic congestion problems when cars exit a motor park. The ACO based on the nature and movement of the natural ants, simulates the movement of cars out of the car park through their nearest choice exit. A car park simulation was also used for the mathematical computation of the pheromone. The system was implemented using SIMD because of its dual parallelization ability. The result showed about 95% increase on the number of vehicles that left the motor park in one second. A clear indication that pheromones are large determinants of the shortest route to take as cars followed the closest exit to them. Future researchers may consider monitoring a centralized tally system for cars coming into the park through a censored gate being.

Research of Fly over as a Solution to Congestion of Intersection Junction(Case Study:Jalan Jatingaleh Semarang)

In the next few years traffic will happen most of the time.This was triggered by the growing rate of vehicles against the road capacity which is not balance.All the time the congestion in the city of Semarang has been occurred at peak hours.Congestion also occurred in between Teuku Umar and Setia Budi road Jatingaleh because of a plot intersection(Kesatrian intersection,PLN intersection and Jatingaleh intersection)with the Toll Road.Jatingaleh is located in the southern city of Semarang which is a central meeting point between the upper and lower Semarang where the vehicle flows in through a combination of local current and regional traffic,and the flow of vehicles coming in and out from highway.The main cause of the problems that occurred in the area of Jatingaleh is due to the numbers of vehicles movement that occurs at the intersections.With the above issues,it is necessary to analyse the existing conditions and look into some solutions.Before carrying out an analysis a field surveys at peak hours for example morning(06:00 to 08:00 am)and for the afternoon(04:00 to 06:00 pm)should be conducted,then the number of vehicles is counted manually with“short-breakcounting”according to types of vehicles.From the analysis we found that the degree of saturation(DS)is 1.61 between Teuku Umar and Setia Budi road during the morning peak hours and 1.56 during the afternoon peak hours.This means that the capacity of the existing road is no longer able to accommodate the traffic flow.One of the solutions for the congestion that occurs at the intersection of Jatingaleh is to apply the efficiency of the intersection that is not in a plot with a Fly over,Underpass and the combination of Fly Over-Underpass.Base on the flow reduction calculation with 3 comparative modeling it shows that the Fly Over is the most technically efficient to be applied in this research.

Reducing congestion and emissions via roadside unit deployment under mixed traffic flow

It is expected that for a long time the future road trafc will be composed of both regular vehicles(RVs)and connected autonomous vehicles(CAVs).As a vehicle-to-infrastructure technology dedicated to facilitating CAV under the mixed trafc fow,roadside units(RSUs)can also improve the quality of information received by CAVs,thereby infuencing the routing behavior of CAV users.This paper explores the possibility of leveraging the RSU deployment to afect the route choices of both CAVs and RVs and the adoption rate of CAVs so as to reduce the network congestion and emissions.To this end,we frst establish a logit-based stochastic user equilibrium model to capture drivers’route choice and vehicle type choice behaviors provided the RSU deployment plan is given.Particularly,CAV users’perception error can be reduced by higher CAV penetration and denser RSUs deployed on the road due to the improved information quality.With the established equilibrium model,the RSU deployment problem is then formulated as a mathematical program with equilibrium constraints.An active-set algorithm is presented to solve the deployment problem efciently.Numerical results suggest that an optimal RSU deployment plan can efectively drive the system towards one with lower network delay and emissions.

Efficient Routing Protocol with Localization Based Priority&Congestion Control for UWSN

The nodes in the sensor network have a wide range of uses,particularly on under-sea links that are skilled for detecting,handling as well as management.The underwater wireless sensor networks support collecting pollution data,mine survey,oceanographic information collection,aided navigation,strategic surveillance,and collection of ocean samples using detectors that are submerged inwater.Localization,congestion routing,and prioritizing the traffic is the major issue in an underwater sensor network.Our scheme differentiates the different types of traffic and gives every type of traffic its requirements which is considered regarding network resource.Minimization of localization error using the proposed angle-based forwarding scheme is explained in this paper.We choose the shortest path to the destination using the fitness function which is calculated based on fault ratio,dispatching of packets,power,and distance among the nodes.This work contemplates congestion conscious forwarding using hard stage and soft stage schemes which reduce the congestion by monitoring the status of the energy and buffer of the nodes and controlling the traffic.The study with the use of the ns3 simulator demonstrated that a given algorithm accomplishes superior performance for loss of packet,delay of latency,and power utilization than the existing algorithms.

Data Center Traffic Scheduling Strategy for Minimization Congestion and Quality of Service Guaranteeing

According to Cisco’s Internet Report 2020 white paper,there will be 29.3 billion connected devices worldwide by 2023,up from 18.4 billion in 2018.5G connections will generate nearly three times more traffic than 4G connections.While bringing a boom to the network,it also presents unprecedented challenges in terms of flow forwarding decisions.The path assignment mechanism used in traditional traffic schedulingmethods tends to cause local network congestion caused by the concentration of elephant flows,resulting in unbalanced network load and degraded quality of service.Using the centralized control of software-defined networks,this study proposes a data center traffic scheduling strategy for minimization congestion and quality of service guaranteeing(MCQG).The ideal transmission path is selected for data flows while considering the network congestion rate and quality of service.Different traffic scheduling strategies are used according to the characteristics of different service types in data centers.Reroute scheduling for elephant flows that tend to cause local congestion.The path evaluation function is formed by the maximum link utilization on the path,the number of elephant flows and the time delay,and the fast merit-seeking capability of the sparrow search algorithm is used to find the path with the lowest actual link overhead as the rerouting path for the elephant flows.It is used to reduce the possibility of local network congestion occurrence.Equal cost multi-path(ECMP)protocols with faster response time are used to schedulemouse flows with shorter duration.Used to guarantee the quality of service of the network.To achieve isolated transmission of various types of data streams.The experimental results show that the proposed strategy has higher throughput,better network load balancing,and better robustness compared to ECMP under different traffic models.In addition,because it can fully utilize the resources in the network,MCQG also outperforms another traffic scheduling strategy that does rerouting for elephant flows(namely Hedera).Compared withECMPandHedera,MCQGimproves average throughput by 11.73%and 4.29%,and normalized total throughput by 6.74%and 2.64%,respectively;MCQG improves link utilization by 23.25%and 15.07%;in addition,the average round-trip delay and packet loss rate fluctuate significantly less than the two compared strategies.

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.

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.

A Fast and Efficient Global Router for Congestion Optimization

An efficient parallel global router using random optimization that is independent of net ordering is proposed.Parallel approaches are described and strategies guaranteeing the routing quality are discussed.The wire length model is implemented on multiprocessor,which enables the algorithm to approach feasibility of large scale problems.Timing driven model on multiprocessor and wire length model on distributed processors are also presented.The parallel algorithm greatly reduces the run time of routing.The experimental results show good speedups with no degradation of the routing quality.

An environment-friendly control method for congestion flow ahead of expressway toll stations

To alleviate the resulting increase in energy consumption and emissions and other issues caused by the traffic congestion ahead of the expressway toll station, a novel traffic flowcontrol method is put forward based on the environment-friendly conception. The technical thinking of inducing the slowly moving traffic into a batch pass is determined based on the conclusion of the research, traffic flowtheory and traffic sensing detection technology. The model of stop times is established and the parameters of the system are optimized in accordance with the principle of minimizing the fuel consumption. The optimal location selection of traffic control lights and Detector 2 for queue of different lengths at toll stations are calculated based on the model. Finally, the effect of the congestion flowcontrol system is verified via the Paramics simulation system. The result shows that the control system is capable of reducing90% of fuel consumption for vehicles going through toll stations.

Analyses of unified congestion measures for interrupted traffic flow on urban roads

To study the congestion of interrupted flow on urban roads, a comprehensive evaluation method is proposed. First, based on the results of correlation analysis between different parameters of interrupted flow, the traffic parameters of interrupted traffic flow are divided into two categories： the basic parameters and the operation parameters. Polynomial regression is used to formulize the nonlinear relationships between the basic parameters and the operation parameters. Then, the congestion model incorporating both operational and volume characteristics of traffic flow is proposed. The inputs of the model are the basic parameters, while the output is a dimensionless index value between 0 and 1. Finally, the proposed methods are compared with existing evaluation measures of congestion. Results show that the proposed indices can capture the variation of both the basic parameters and the operation parameters, which is more balanced compared with the existing evaluation measures.

The comprehensive measure model for urban traffic congestion based on value function

According to the distribution characteristics of traffic congestion in time and space, a measure index system of urban traffic congestion is set up based on the spatial and temporal distribution. Based on the analysis of the main characteristics of traffic congestion and the generation process of traffic congestion, the measure model for urban traffic congestion is constructed by the value function. Moreover, based on the measure values of traffic congestion in urban road networks with defined different levels, a method to prevent and control traffic congestion is designed. The application results confirm that the proposed method is feasible in comprehensive measures for urban traffic congestion and they are consistent with the results of other methods. The measuring results can therefore reflect the actual situation. The comprehensive measure model is scientific and the process is simple, and it has wide application prospects and practical value.

Dynamic traffic congestion pricing and electric vehicle charging management system for the internet of vehicles in smart cities

The integration of the Internet of Vehicles(IoV)in future smart cities could help solve many traffic-related challenges,such as reducing traffic congestion and traffic accidents.Various congestion pricing and electric vehicle charging policies have been introduced in recent years.Nonetheless,the majority of these schemes emphasize penalizing the vehicles that opt to take the congested roads or charge in the crowded charging station and do not reward the vehicles that cooperate with the traffic management system.In this paper,we propose a novel dynamic traffic congestion pricing and electric vehicle charging management system for the internet of vehicles in an urban smart city environment.The proposed system rewards the drivers that opt to take alternative congested-free ways and congested-free charging stations.We propose a token management system that serves as a virtual currency,where the vehicles earn these tokens if they take alternative non-congested ways and charging stations and use the tokens to pay for the charging fees.The proposed system is designed for Vehicular Ad-hoc Networks(VANETs)in the context of a smart city environment without the need to set up any expensive toll collection stations.Through large-scale traffic simulation in different smart city scenarios,it is proved that the system can reduce the traffic congestion and the total charging time at the charging stations.

Evolution of Road Traffic Congestion Control:A Survey from Perspective of Sensing,Communication,and Computation

Road traffic congestion can inevitably de-grade road infrastructure and decrease travel efficiency in urban traffic networks,which can be relieved by employing appropriate congestion control.Accord-ing to different developmental driving forces,in this paper,the evolution of road traffic congestion control is divided into two stages.The ever-growing num-ber of advanced sensing techniques can be seen as the key driving force of the first stage,called the sens-ing stage,in which congestion control strategies ex-perienced rapid growth owing to the accessibility of traffic data.At the second stage,i.e.,the communica-tion stage,communication and computation capabil-ity can be regarded as the identifying symbols for this stage,where the ability of collecting finer-grained in-sight into transportation and mobility reality improves dramatically with advances in vehicular networks,Big Data,and artificial intelligence.Specifically,as the pre-requisite for congestion control,in this paper,ex-isting congestion detection techniques are first elab-orated and classified.Then,a comprehensive survey of the recent advances for current congestion control strategies with a focus on traffic signal control,vehi-cle route guidance,and their combined techniques is provided.In this regard,the evolution of these strate-gies with continuous development of sensing,com-munication,and computation capability are also intro-duced.Finally,the paper concludes with several re-search challenges and trends to fully promote the in-tegration of advanced techniques for traffic congestion mitigation in transportation systems.

Analysis and Taxonomy of Congestion Control Mechanisms for Internet Reliable Multicast

The research of congestion control for Internet reliable multicast is one of the most active fields in reliable multicast protocol research. Many reliable multicast congestion control mechanisms have been put forward. In this paper we present principal problems of congestion control for Internet reliable multicast, analyze solutions and difficulties of solving these problems, and then give a classification of some reliable multicast congestion control mechanisms. Lastly the future work is proposed.