Congestion control with AQM and dynamic quantisers

Stable Queue Management in communication networks

This paper is concerned with the design of robust active queue management (AQM) controllers for a class of TCP networks. In TCP/IP networks, the packet-dropping probability function is limited between 0 and 1. Therefore, a TCP network with AQM controller was modeled as a rate-based non-linear system with a saturated input. The nonlinear output feedback AQM controller is proposed for achieving the desired queue size and guaranteeing asymptotic stability of the operating point. The performance and effectiveness of the proposed control laws are validated for serial network scenarios through numerical simulations by Network Simulator-2 (NS-2). Simulation results confirm that the proposed scheme outperforms other AQM schemes.

Review of Queue Management in Packet Switched Networks

Congestion tracking control for multi-router TCP/AQM network based on integral backstepping

Congestion is an important issue which researchers focus on in the Transmission Control Protocol (TCP) network environment. To keep the stability of the whole network, congestion control algorithms have been extensively studied. Queue management method employed by the routers is one of the important issues in the congestion control study. Active Queue Management (AQM) has been proposed as a router-based mechanism for early detection of congestion inside the network. In this study, we are comparing AQM two popular queue management methods, Random Early Detection (RED) and droptail, in different aspects, such as throughput and fairness Index. The comparison results indicate RED performed slightly better with higher throughput and higher fairness Index than droptail. Simulation is done by using Network Simulator (NS2) and the graphs are drawn using X- graph.

Active queue management (AQM) has been widely used for congestion avoidance in transmission control protocol (TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we propose a novel adaptive AQM(active queue management ) algorithm for TCP network to cope with the network delay and time-varying network parameters based on RBF-PID controller, the RBF(redial basis function) neural network is employed to automatically tune the controller's parameters according to link capacity, traffic load and transmitting time-delay, which makes the presented AQM algorithm perform well for a wide-range of network conditions. The simulation results have shown that the RBF-PID-based AQM is feasible and efficient, and yields superior performance with faster transient time and better adaptive ability compared to the proportional-integral (PI)-based AQM.

Active Queue Management in Wireless Networks by Using Nonlinear Extended Network Disturbance

In recent years industrial control systems using networks for communication and Transmission Control Protocol (TCP) are normally used in supervisory layer, so malicious outsider and insider can attack through network. One of useful based model methods for fault detection and isolation is Unknown Input Observers (UIO). Some previous works that used UIO, observe dynamic of the physical system to detect attacks. This paper first describes how attacker can make Denial of Service (DoS) in active queue management and by using UIO, designed Network Intrusion Detection System (NIDS) that use fluid flow model, then fusion information of NIDS and Host Intrusion Detection Systems (HIDS). Distributed Intrusion Detection System (DIDS), detects abnormal behavior of network and physical system and alarms for three state: free attack, DoS and deception attack. So false negative for free attack and false positive for DoS attack are being reduced. Simulation results demonstrate the high success level of this approach for detecting attacks.

In Internet gateways with active queue management, effective algorithms are often used to enhance the traffic flows through the gateway. The random early detection (RED) algorithm is a widely used algorithm for controlling the transmission control protocol (TCP) flows. Specifically, the RED algorithm has deliberately introduced randomness into the explicit congestion notification (ECN) marking mechanism in order to enhance the fairness and to avoid synchronization of TCP flows through the gateway. As randomness plays a key role in providing better performance for RED gateways than the DropTail gateways, knowledge of the effect of the random mechanism is important to the understanding the behavior of the system. The fluid flow model (FFM), ignoring the randomness of ECN markings, has provided a fast alternative to the slow ns-2 network simulation tool in studying the TCP flow in the RED gateway. In this brief, the random ECN marking mechanism in RED gateways has been studied. The randomness of the RED ECN marking algorithm is implemented into the FFM. Verified using ns-2 simulations, the proposed model shows better dynamical performance than FFM in both the single-bottleneck dumbbell network and in networks with interactive bottlenecks.

Queue delay estimation and its application to TCP Vegas

In deep space missions, large-scale deep space information and continuous sensory data are generated, processed, and exchanged over Internet of deep space things (IoDST). Ensuring reliable communication in IoDST requires resolution of challenges engendered by the unique characteristics of IoDST, including long propagation delays, link outages, high error rates, and asymmetric bandwidths. Thus, transmission control protocol (TCP) layer functionalities are crucial for ensuring reliable IoDST communications. However, existing TCP congestion control (CC) protocols present poor performance in IoDST communications, owing to the dependence of traditional window-based CC approaches on pre-configured rules to adjust transmission rate against the aforementioned unique characteristics. In this paper, we propose an intelligent CC scheme called optimistic actor–critic-based TCP congestion control (OAC-TCPCC) to solve the problems of the challenging link conditions in IoDST. OAC-TCPCC dynamically determines optimal congestion window for data transmission over IoDST communication links to maximize the TCP throughput performance and minimize file transfer time. Simulation results reveal that OAC-TCPCC improves the TCP throughput performance by up to 27%, 79%, 92%, 477%, 643%, and 766%; and reduces file transfer time by up to 16%, 37%, 50%, 48%, 58%, and 79%, compared to DRL-CC, TP-Planet, FAST TCP, TCP Peach, TCP BBR, and TCP CUBIC, respectively.

Long Term Evolution (LTE) evolved Node Bs (eNB) have dedicated buffers for each Radio Access Bearer (RAB) implemented at the Packet Data Convergence Protocol (PDCP) layer to receive and prepare user data for transmission over the air interface. These buffers multiplex the connections established by the active applications of a single user. Modern applications use the Transmission Control Protocol (TCP) that has a greedy mechanism to transfer data by trying to use all the available resources. If not managed, TCP sources may send large bursts that may eventually overload the PDCP buffer causing tail drops and quality degradation. In order to prevent these incidents, buffer management mechanisms are required. As this paper shows, neither the standard 3GPP Discard Timer nor the conventional Active Queue Management (AQM) techniques are able to properly manage the PDCP buffer. As a solution, two alternative mechanisms are proposed, which are more suited to the PDCP specific environment. Their superior performance is shown with detailed simulations.

A robust PID and RLS controller for TCP/AQM system

Design of a fuzzy controller for active queue management

Classical Transmission Control Protocol (TCP) designs have never considered the identity of the competing transport protocol as useful information to TCP sources in congestion control mechanisms. When competing against a TCP flow on a bottleneck link, a User Datagram Protocol (UDP) flow can unfairly occupy the entire link bandwidth and suffocate all TCP flows on the link. If it were possible for a TCP source to know the type of transport protocol that deprives it of link access, perhaps it would be better for the TCP source to react in a way which prevents total starvation. In this paper, we use coefficient of variation and power spectral density of throughput traces to identify the presence of UDP transport protocols that compete against TCP flows on bottleneck links. Our results show clear traits that differentiate the presence of competing UDP flows from TCP flows independent of round-trip times variations. Signatures that we identified include an increase in coefficient of variation whenever a competing UDP flow joins the bottleneck link for the first time, noisy spectral density representation of a TCP flow when competing against a UDP flow in the bottleneck link, and a dominant frequency with outstanding power in the presence of TCP competition only. In addition, the results show that signatures for congestion caused by competing UDP flows are different from signatures due to congestion caused by competing TCP flows regardless of their round-trip times. The results in this paper present the first steps towards development of more ’intelligent’ congestion control algorithms with added capability of knowing the identity of aggressor protocols against TCP, and subsequently using this additional information for rate control.