Currently, the most advanced framework for stochastic network calculus is the min-plus algebra, providing bounds for the end-to-end delay in networks. The bounds calculated with the min-plus algebra are tight, if compared with previous methods, but we still observe a significant degradation of the tightness of bounds as the number of nodes crossed by flows increases. Moreover, even if the calculations are greatly simplified relatively to previous methods, they are still complicated as numerical optimizations are necessary. In this paper, we propose a novel framework for the approximated calculation of end-to-end delay: the bounded-variance network calculus, by which we provide two important results. Firstly, we obtain an evaluation of end-to-end delay significantly tighter than that offered by the min-plus algebra. Secondly, the calculations needed to compute our approximations of delay are much simpler and we show that in a typical application scenario used to test the accuracy of the frameworks for network calculus, our approximations are obtained in a closed analytical form, as opposed to the numerical bounds of the other methods. These two advantages constitute an important progress in the direction of evolving statistical network calculus into a practical tool for network analysis.
Long-range dependence (LRD) is a largely verified property of Internet traffic, which severely affects queuing performance in network buffers. A common approach for guaranteeing performance requirements is to control the statistical profile of the input traffic by regulators based on the leaky bucket scheme. In this paper, we investigate by simulation how the 1/f α power-law spectrum of LRD traffic is altered when traffic is regulated by a leaky bucket policer. Analysis of the traffic spectral characteristics is carried out mainly by means of the Modified Allan Variance, a time-domain quantity with demonstrated superior accuracy in fractional-noise parameter estimation, recently introduced also for traffic analysis. This approach allows to get a finer insight into power-law spectral characteristics of policed traffic. We also investigate some other properties of the leaky bucket fed with LRD traffic, such as its dropping probability and its effect on queuing delay in a following FIFO scheduler.Index Terms Communication system traffic, fractional noise, Internet, long-range dependence, queuing analysis, traffic control (communication).
Long-range dependence (LRD) is a widely verified property of traffic crossing the wireless LAN radio interface. LRD severely affects network performance yielding longer queuing delays. In this paper, we study how LRD and non-LRD traffic flows influence each other in the IEEE 802.11e wireless access network and their queuing behaviour in downstream schedulers. We consider scenarios with one and two wireless hops. We investigate interaction of traffic flows with the service class separation enabled by the IEEE 802.11e EDCA function, comparing results with those of the basic scenario with a single service class shared by all traffic flows. We find that a partial isolation of service classes is enabled by the IEEE 802.11e access function. However, competing flows exhibit a queuing behavior, in downstream schedulers, which cannot be accounted for by standard LRD traffic descriptors.Index Terms Communication system traffic, long-range dependence, quality of service, queuing analysis, traffic control (communication), wireless LAN.
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