838 resultados para network congestion control


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Existing approaches for multirate multicast congestion control are either friendly to TCP only over large time scales or introduce unfortunate side effects, such as significant control traffic, wasted bandwidth, or the need for modifications to existing routers. We advocate a layered multicast approach in which steady-state receiver reception rates emulate the classical TCP sawtooth derived from additive-increase, multiplicative decrease (AIMD) principles. Our approach introduces the concept of dynamic stair layers to simulate various rates of additive increase for receivers with heterogeneous round-trip times (RTTs), facilitated by a minimal amount of IGMP control traffic. We employ a mix of cumulative and non-cumulative layering to minimize the amount of excess bandwidth consumed by receivers operating asynchronously behind a shared bottleneck. We integrate these techniques together into a congestion control scheme called STAIR which is amenable to those multicast applications which can make effective use of arbitrary and time-varying subscription levels.

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A significant impediment to deployment of multicast services is the daunting technical complexity of developing, testing and validating congestion control protocols fit for wide-area deployment. Protocols such as pgmcc and TFMCC have recently made considerable progress on the single rate case, i.e. where one dynamic reception rate is maintained for all receivers in the session. However, these protocols have limited applicability, since scaling to session sizes beyond tens of participants necessitates the use of multiple rate protocols. Unfortunately, while existing multiple rate protocols exhibit better scalability, they are both less mature than single rate protocols and suffer from high complexity. We propose a new approach to multiple rate congestion control that leverages proven single rate congestion control methods by orchestrating an ensemble of independently controlled single rate sessions. We describe SMCC, a new multiple rate equation-based congestion control algorithm for layered multicast sessions that employs TFMCC as the primary underlying control mechanism for each layer. SMCC combines the benefits of TFMCC (smooth rate control, equation-based TCP friendliness) with the scalability and flexibility of multiple rates to provide a sound multiple rate multicast congestion control policy.

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The increasing diversity of Internet application requirements has spurred recent interest in transport protocols with flexible transmission controls. In window-based congestion control schemes, increase rules determine how to probe available bandwidth, whereas decrease rules determine how to back off when losses due to congestion are detected. The control rules are parameterized so as to ensure that the resulting protocol is TCP-friendly in terms of the relationship between throughput and loss rate. This paper presents a comprehensive study of a new spectrum of window-based congestion controls, which are TCP-friendly as well as TCP-compatible under RED. Our controls utilize history information in their control rules. By doing so, they improve the transient behavior, compared to recently proposed slowly-responsive congestion controls such as general AIMD and binomial controls. Our controls can achieve better tradeoffs among smoothness, aggressiveness, and responsiveness, and they can achieve faster convergence. We demonstrate analytically and through extensive ns simulations the steady-state and transient behavior of several instances of this new spectrum.

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This thesis presents a framework for aggregated congestion management for TCP flows and shows how to integrate such an approach in an existing TCP protocol stack. The thesis presents an initial implementation of this congestion management scheme in Linux, with performance evaluation in ns as well.

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In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

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A number of commonly encountered simple neural network types are discussed, with particular attention being paid to their applicability in automation and control when applied to food processing. In the first instance n-tuple networks are considered, these being particularly useful for high speed production checking operations. Subsequently backpropagation networks are discussed, these being useful both in a more familiar feedback control arrangement and also for such things as recipe prediction.

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Mode of access: Internet.

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Dedicated short range communications (DSRC) was proposed for collaborative safety applications (CSA) in vehicle communications. In this article we propose two adaptive congestion control schemes for DSRC-based CSA. A cross-layer design approach is used with congestion detection at the MAC layer and traffic rate control at the application layer. Simulation results show the effectiveness of the proposed rate control scheme for adapting to dynamic traffic loads.

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In this paper, a congestion control mechanism is presented for multiservice wireless OFDMA networks. The revenue rate and the user SNR's are used to partition the bandwidth in accordance with a complete partitioning structure. Moreover, through the use of our scheme the QoS of any ongoing connections can be satisfied. Results show that the revenue rate plays an important role in prioritizing the different services. © 2013 Springer Science+Business Media New York.

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NS2作为开源软件缺少对最新研究算法的模拟能力 .在现有软件基础上对其进行功能扩展极其必要 ,是模拟研究新理论新算法的基础 .本文着重探讨网络仿真软件 NS2的功能扩展原理及设计实现 ,展示运用 NS2仿真器对网络行为进行研究的过程 .最后对该算法进行模拟实验 ,并与已有 RED和 PI算法进行性能对比分析 .

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In this paper, a rate-based flow control scheme based upon per-VC virtual queuing is proposed for the Available Bit Rate (ABR) service in ATM. In this scheme, each VC in a shared buffer is assigned a virtual queue, which is a counter. To achieve a specific kind of fairness, an appropriate scheduler is applied to the virtual queues. Each VC's bottleneck rate (fair share) is derived from its virtual cell departure rate. This approach of deriving a VC's fair share is simple and accurate. By controlling each VC with respect to its virtual queue and queue build-up in the shared buffer, network congestion is avoided. The principle of the control scheme is first illustrated by max–min flow control, which is realised by scheduling the virtual queues in round-robin. Further application of the control scheme is demonstrated with the achievement of weighted fairness through weighted round robin scheduling. Simulation results show that with a simple computation, the proposed scheme achieves the desired fairness exactly and controls network congestion effectively.

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A high performance, low computational complexity rate-based flow control algorithm which can avoid congestion and achieve fairness is important to ATM available bit rate service. The explicit rate allocation algorithm proposed by Kalampoukas et al. is designed to achieve max–min fairness in ATM networks. It has several attractive features, such as a fixed computational complexity of O(1) and the guaranteed convergence to max–min fairness. In this paper, certain drawbacks of the algorithm, such as the severe overload of an outgoing link during transient period and the non-conforming use of the current cell rate field in a resource management cell, have been identified and analysed; a new algorithm which overcomes these drawbacks is proposed. The proposed algorithm simplifies the rate computation as well. Compared with Kalampoukas's algorithm, it has better performance in terms of congestion avoidance and smoothness of rate allocation.