Fluid-flow approximation is an approach to modelling and evaluating the performance of vast computer networks. Due to varying traffic and performance of transmission protocols reacting to traffic overloads, computer networks are in a permanent transient state. The fluid-flow method main advantage is its ability to analyse these transient states. The article reviews and organises several versions of this approach, indicating a few errors. The main reason for these errors is confusion or lack of distinction between the two versions of the Internet Protocol – when the queue of packets at a node is too long, they may be destroyed or only marked as redundant. The paper compares and evaluates these fluid-flow approximation models with mild and aggressive settings of RED parameters. The authors build a software system with hitherto unprecedented capabilities regarding the size of the networks to be analysed and with innovative way of organising the calculations. The paper shows how large differences imprecise assumptions can introduce in quantitative results.
As the traffic volume from various Internet of things (IoT) networks increases significantly, the need for adapting the quality of service (QoS) mechanisms to the new Internet conditions becomes essential. We propose a QoS mechanism for the IoT gateway based on packet classification and active queue management (AQM). End devices label packets with a special packet field (type of service (ToS) for IPv4 or traffic class (TC) for IPv6) and thus classify them as priority for real-time IoT traffic and non-priority for standard IP traffic. Our AQM mechanism drops only non-priority packets and thus ensures that real-time traffic packets for critical IoT systems are not removed if the priority traffic does not exceed the maximum queue capacity. This AQM mechanism is based on the PIα controller with non-integer integration order. We use fluid flow approximation and discrete event simulation to determine the influence of the AQM policy on the packet loss probability, queue length and its variability. The impact of the long-range dependent (LRD) traffic is also considered. The obtained results show the properties of the proposed mechanism and the merits of the PIα controller.
The article proposes a model in which Diffusion Approximation is used to analyse the TCP/AQM transmission mechanism in a multinode computer network. In order to prevent traffic congestion, routers implement AQM (Active Queue Management) algorithms. We investigate the influence of using RED-based AQM mechanisms and the fractional controller PIγ on the transport layer. Additionally, we examine the cases in which the TCP and the UDP flows occur and analyse their mutual influence. Both transport protocols used are independent and work simultaneously. We compare our solution with the Fluid Flow approximation, demonstrating the advantages of Diffusion Approximation.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.