2,582 research outputs found

    A genetic algorithm for the design of a fuzzy controller for active queue management

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    Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

    GA-PSO-Optimized Neural-Based Control Scheme for Adaptive Congestion Control to Improve Performance in Multimedia Applications

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    Active queue control aims to improve the overall communication network throughput while providing lower delay and small packet loss rate. The basic idea is to actively trigger packet dropping (or marking provided by explicit congestion notification (ECN)) before buffer overflow. In this paper, two artificial neural networks (ANN)-based control schemes are proposed for adaptive queue control in TCP communication networks. The structure of these controllers is optimized using genetic algorithm (GA) and the output weights of ANNs are optimized using particle swarm optimization (PSO) algorithm. The controllers are radial bias function (RBF)-based, but to improve the robustness of RBF controller, an error-integral term is added to RBF equation in the second scheme. Experimental results show that GA- PSO-optimized improved RBF (I-RBF) model controls network congestion effectively in terms of link utilization with a low packet loss rate and outperform Drop Tail, proportional-integral (PI), random exponential marking (REM), and adaptive random early detection (ARED) controllers.Comment: arXiv admin note: text overlap with arXiv:1711.0635

    Adaptive Active Queue Management based on Queue Ratio of Set-point Weighting

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    Presently, active queue management (AQM) is one of the important considerations in communication networks. The challenge is to make it simple and robust in bursty traffic and uncertain network conditions. This paper proposes a new AQM scheme, an adaptive ratio proportional integral (ARPI), for adaptively controlling network congestion in dynamic network traffic conditions. First, AQM was designed by adding a set-point weighting structure to a proportional integral (PI) controller to reduce the burstiness of network traffic. Second, an adaptive set-point weighting based on the ratio of instantaneous queue length to the set-point queue and the buffer size was proposed to improve the robustness of a non-linear network. The proposed design integrates the aforementioned expectations into one function and needs only one parameter change to adapt to fluctuating network condition. Hence, this scheme provides lightweight computation and simple software and hardware implementation. This approach was analyzed and compared with the PI AQM scheme. Evaluation results demonstrated that our proposed AQM can regulate queue length with a fast response, good stability under any traffic conditions, and small queuing delay

    A variable structure control approach to active queue management for TCP with ECN

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    Cataloged from PDF version of article.It has been shown that the transmission control protocol (TCP) connections through the congested routers can be modeled as a feedback dynamic system. In this paper, we design a variable structure (VS) based control scheme in active queue management (AQM) supporting explicit congestion notification (ECN). By analyzing the robustness and performance of the control scheme for the nonlinear TCP/AQM model, we show that the proposed design has good performance and robustness with respect to the uncertainties of the round-trip time (RTT) and the number of active TCP sessions, which are central to the notion of AQM. Implementation issues are discussed and ns simulations are provided to validate the design and compare its performance to other peer schemes’ in different scenarios. The results show that the proposed design significantly outperforms the peer AQM schemes in terms of packet loss ratio, throughput and buffer fluctuation

    An Improved Link Model for Window Flow Control and Its Application to FAST TCP

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    This paper presents a link model which captures the queue dynamics in response to a change in a transmission control protocol (TCP) source's congestion window. By considering both self-clocking and the link integrator effect, the model generalizes existing models and is shown to be more accurate by both open loop and closed loop packet level simulations. It reduces to the known static link model when flows' round trip delays are identical, and approximates the standard integrator link model when there is significant cross traffic. We apply this model to the stability analysis of fast active queue management scalable TCP (FAST TCP) including its filter dynamics. Under this model, the FAST control law is linearly stable for a single bottleneck link with an arbitrary distribution of round trip delays. This result resolves the notable discrepancy between empirical observations and previous theoretical predictions. The analysis highlights the critical role of self-clocking in TCP stability, and the proof technique is new and less conservative than existing ones

    FAST TCP: Motivation, Architecture, Algorithms, Performance

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    We describe FAST TCP, a new TCP congestion control algorithm for high-speed long-latency networks, from design to implementation. We highlight the approach taken by FAST TCP to address the four difficulties which the current TCP implementation has at large windows. We describe the architecture and summarize some of the algorithms implemented in our prototype. We characterize its equilibrium and stability properties. We evaluate it experimentally in terms of throughput, fairness, stability, and responsiveness
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