Distributed Congestion Control Algorithm Research Articles

Deep Reinforcement Learning-Based Distributed Congestion Control in Cellular V2X Networks

Distributed congestion control (DCC) improves system performance by lowering channel congestion in vehicular environments with high vehicle density. The 3rd Generation Partnership Project standard defines the related metrics of channel busy ratio (CBR) and introduces possible rate and power control mechanisms to mitigate channel congestion in cellular vehicle-to-everything (C-V2X) sidelink. However, the DCC of C-V2X is not sufficiently specified to implement these controls. In this letter, we propose a novel DCC algorithm based on deep reinforcement learning (DRL) to improve congestion control performance in C-V2X sidelink. The proposed algorithm allows the DRL agent to observe a CBR state and select the packet transmission rate that can maximize the reward of packet delivery rate (PDR) while maintaining higher channel utilization. Simulation results show that the proposed algorithm provides performance gain in terms of PDR and sidelink throughput compared with the existing DCC method.

On the Bottleneck Structure of Congestion-Controlled Networks

In this paper,we introduce the Theory of Bottleneck Ordering, a mathematical framework that reveals the bottleneck structure of data networks. This theoretical framework provides insights into the inherent topological properties of a network in at least three areas: (1) It identifies the regions of influence of each bottleneck; (2) it reveals the order in which bottlenecks (and flows traversing them) converge to their steady state transmission rates in distributed congestion control algorithms; and (3) it provides key insights into the design of optimized traffic engineering policies. We demonstrate the efficacy of the proposed theory in TCP congestion-controlled networks for two broad classes of algorithms: Congestion-based algorithms (TCP BBR) and loss-based additive-increase/multiplicative-decrease algorithms (TCP Cubic and Reno). Among other results, our network experiments show that: (1) Qualitatively, both classes of congestion control algorithms behave as predicted by the bottleneck structure of the network; (2) flows compete for bandwidth only with other flows operating at the same bottleneck level; (3) BBR flows achieve higher performance and fairness than Cubic and Reno flows due to their ability to operate at the right bottleneck level; (4) the bottleneck structure of a network is continuously changing and its levels can be folded due to variations in the flows' round trip times; and (5) against conventional wisdom, low-hitter flows can have a large impact to the overall performance of a network.

Congestion Free Routing Mechanism for IoT-Enabled Wireless Sensor Networks for Smart Healthcare Applications

Recently, the Internet of Things (IoT) topology has used to collect physical, physiological, vital signs of patients in consumer-centric e-health or consumer' wellness care services. In such healthcare systems, varieties of medical sensors are attached to the patients to collect vital signs from those who are under observation. The data gathering process in IoT-enabled Wireless Sensor Network (WSN) suffers from the congestion problem. The effect of this translates on missing packets, a decrease of reliability and throughput degradation in IoT-enabled WSN. This article proposes a distributed congestion control algorithm for IoT-enabled WSNs to effectively resolve the congestion for healthcare applications. The proposed scheme alleviates congestion by a priority-based data routing strategy. Furthermore, this article presents a priority queue based scheduling scheme for better reliability. We analyze the properties of the proposed congestion control mechanism mathematically and validate its performance through extensive simulation and real-life experiments. The application of this work can be used to an early warning system in detecting abnormal heart rate, blood pressure, ECG, EMG in the hospital/home care environment to the state-of-art diagnosis.

Channel-Aware Congestion Control in Vehicular Cyber-Physical Systems

In vehicular cyber-physical systems, cars are connected to create a mobile network called a vehicular ad hoc network (VANET) to perform various functions, including improved awareness of the surrounding environment. Moving vehicles continually broadcast beacon signals containing information such as position, heading, acceleration, steering angle, vehicle size, and accident notification. However, channel congestion in dense traffic conditions adversely affects network performance. To resolve congestion in VANETs, several works in the literature have studied congestion control. However, they have considered packet loss only as an indication of channel congestion regardless of channel condition. In this paper, we present a channel-aware congestion control algorithm (CACC) that controls the transmission power and data rate. We take into account the received signal strength (RSS) when diagnosing packet loss to determine channel conditions, such as severe fading or channel congestion. In the case of severe fading, we decrease the data rate for a more robust modulation and coding scheme. Additionally, we adjust the transmission power to maintain a desirable packet error rate. Our simulation results show that CACC significantly outperforms other distributed congestion control algorithms by reducing the packet loss rate and increasing the packet delivery ratio.

On the Bottleneck Structure of Congestion-Controlled Networks

In this paper, we introduce theTheory of Bottleneck Ordering, a mathematical framework that reveals the bottleneck structure of data networks. This theoretical framework provides insights into the inherent topological properties of a network in at least three areas: (1) It identifies the regions of influence of each bottleneck; (2) it reveals the order in which bottlenecks (and flows traversing them) converge to their steady state transmission rates in distributed congestion control algorithms; and (3) it provides key insights into the design of optimized traffic engineering policies. We demonstrate the efficacy of the proposed theory in TCP congestion-controlled networks for two broad classes of algorithms: Congestion-based algorithms (TCP BBR) and loss-based additive-increase/multiplicative-decrease algorithms (TCP Cubic and Reno). Among other results, our network experiments show that: (1) Qualitatively, both classes of congestion control algorithms behave as predicted by the bottleneck structure of the network; (2) flows compete for bandwidth only with other flows operating at the same bottleneck level; (3) BBR flows achieve higher performance and fairness than Cubic and Reno flows due to their ability to operate at the right bottleneck level; (4) the bottleneck structure of a network is continuously changing and its levels can be folded due to variations in the flows' round trip times; and (5) against conventional wisdom, low-hitter flows can have a large impact to the overall performance of a network.

Congestion Control Techniques in WSNs: A Review

Congestion control has a great importance in wireless sensor network (WSN), where efficient application of congestion control mechanisms can prolong the network lifetime. Thus, proper examination is needed to improve more refine way to address the congestion occurrence and resolution. While designing congestion control techniques, the maximum output can be achieved by efficient utilization of required resources within WSN. From last few years several approaches have been brought in, that consist of routing protocols which provide support with congestion control, congestion prevention, and reliable data routing. In old schemes the topology reset and extent traffic drop take place because sink node executes the congestion avoidance. Therefore, node level congestion avoidance, detection, congestion preventing, and resolution mechanisms have been proposed during past few years. Our paper provides a brief overview and performance comparison of centralized and distributed congestion control algorithms in WSN.

Less is more: need to simplify ETSI distributed congestion control algorithm

In the European Telecommunication Standards Institute (ETSI) framework, the vehicle-to-vehicle (V2V) and the vehicle-to-roadside (V2R) communications on the 5 GHz frequency band must use the decentralised congestion control (DCC) algorithm standardised by the ETSI. The DCC algorithm distinguishes itself from other methods in that it simultaneously regulates no less than four parameters that all work to the identical effects. However, it is have claimed that this apparently reassuring feature is actually excessive and can lead DCC to perform sub-optimally. It is shown that it could be simplified to use fewer parameters by demonstrating that a physical layer data rate control, which is only one of the four used by the DCC, achieves a better result.

Distributed Congestion Control of Scalable Video Streams

The paper addresses the problem of distributed congestion control in networks where several video stream- ing sessions share joint bottleneck channels. Based on the rate-distortion characteristics of the video streams as well as the requirements of heterogeneous streaming clients, the proposed algorithm determines the utility of rate in- crements in terms of overall quality benefits. We build on the utility-based congestion control framework initially proposed by Kelly (1), (2) and extend it such that it could efficiently handle heterogeneous delays in the network as well as the specific requirements of video streams. We then describe an original implementation of the proposed distributed congestion control algorithm using the common RTP/UDP/IP protocol stack for the efficient streaming of scalable video streams. Each video session independently adapts its streaming rate based on receiver feedbacks, which permits extension to large scale system without central coordination. Finally, we provide extensive simulation results that demonstrate the performance of the proposed solution. It is shown to successfully distribute the network resources among the different sessions such that the overall video quality is maximized. Experiments further demonstrate that the proposed scheme fairly cohabits with TCP, which is certainly an important advantage in today's network architectures.

Traffic management in wireless sensor networks: Decoupling congestion control and fairness

In this paper, we propose a distributed congestion control algorithm for tree based communications in wireless sensor networks, that seeks to adaptively assign a fair and efficient transmission rate to each node. In our algorithm, each node monitors its aggregate output and input traffic rate. Based on the difference of the two, a node then decides to increase (if the output rate is more) or decrease (if the input rate is more) the bandwidth allocable to a flow originating from itself and to those being routed through it. Since the application requirements in sensor network follow no common trait, our design abstracts the notion of fairness, allowing for the development of a generic utility controlling module. Such separation of the utility and fairness controlling modules enable each one to use a separate control law, thereby portraying a more flexible design. The working of our congestion control is independent of the underlying routing algorithm and is designed to adapt to changes in the underlying routing topology. We evaluate the performance of the algorithm via extensive simulations using an event-driven packet level simulator. The results suggest that the proposed protocol acquires a significantly high goodput of around 95% of the actual transmission rate, converges quickly to the optimal rate, and attains the desired fairness.

MACRE: a Novel Distributed Congestion Control Algorithm in DTN

Congestion control is a very important problem which can affect network performance directly. However, owing to the lack of steady end-to-end connection and high latency, the traditional congestion control mechanism based on end-to-end feedback is not feasible in DTN. Because obtaining the global information of network is difficult, the congestion control decisions should be made autonomously with local information only. We propose a novel distributed congestion control algorithm based on epidemic routing protocols----MACRE (Message Admission Control based on Rate Estimation). Preliminary experimental results show that this congestion control mechanism can improve the network performance efficiently.

Distributed bandwidth allocation based on alternating evolution algorithm

In a network, end nodes have to compete for bandwidth through some distributed congestion control algorithms. It is a great challenge to ensure the efficiency and fairness of the distributed control algorithms. TCP congestion control algorithms do not perform well in terms of their efficiency and fairness in high speed networks. In this paper, we propose a novel asymptotic evolution algorithm based on the Logistic Model to allocate limited bandwidth resource. The algorithm introduces an explicit bandwidth pre-allocation factor. The factor is carried by the packet and is computed in routers based on the information of the router capacity, the aggregate load, and the instantaneous queue length; therefore the algorithm does not require the routers to keep the per-flow state. According to this pre-allocation bandwidth factor, the senders asymptotically adjust their sending rate and the bandwidth factor changes asymptotically along with the variation of the aggregate load and the queue length in the routers; therefore the sending rate and the pre-allocation bandwidth factor form alternating evolution and eventually reach a steady state. Theoretical analysis and simulation experiments were conducted to compare our algorithm with related ones. The results show that our algorithm not only provides fast convergence to efficiency and fairness, but also keeps a strong robustness against crossing traffic.

Linear stability of TCP/RED and a scalable control

We demonstrate that the dynamic behavior of queue and average window is determined predominantly by the stability of TCP/RED, not by AIMD probing nor noise traffic. We develop a general multi-link multi-source model for TCP/RED and derive a local stability condition in the case of a single link with heterogeneous sources. We validate our model with simulations and illustrate the stability region of TCP/RED. These results suggest that TCP/RED becomes unstable when delay increases, or more strikingly, when link capacity increases. The analysis illustrates the difficulty of setting RED parameters to stabilize TCP: they can be tuned to improve stability, but only at the cost of large queues even when they are dynamically adjusted. Finally, we present a simple distributed congestion control algorithm that maintains stability for arbitrary network delay, capacity, load and topology.