The paper presents an envelope process which is a deterministic function bounding a stochastic process for a FARIMA traffic model. The envelope process is defined by FARIMA parameters (d associated with Hurst parameter, ϕ or θ) and considered exceed probability ε , which determines the accuracy of the envelope process. The results obtained allow for analytical modeling of network behaviour fed ...

Improving forecasting especially time series forecasting accuracy is an important yet often difficult task facing forecasters. Fuzzy autoregressive integrated moving average (FARIMA) models are the fuzzy improved version of the autoregressive integrated moving average (ARIMA) models, proposed in order to overcome limitations of the traditional ARIMA models; especially data limitation, and yield...

 FARIMA(p,d,q) model is a good traffic model capable of capturing both the long-range and short-range behavior of a network traffic stream in time. In this paper, we propose a prediction-based admission control algorithm for integrated service packet network. We suggest a method to simplify the FARIMA model fitting procedure and hence to reduce the time of traffic modeling and prediction. Our ...

Numerous investigations have revealed that the packet network traffic is bursty and highly correlated. If many large bursts meet in a single queue an overflow is unavoidable even for a slightly loaded network, therefore shaping packet traffic becomes a crucial issue. One of the most commonly used traffic shaping algorithms is a leaky bucket. An important property of a leaky bucket algorithm is ...

The intensity of long-range dependence (LRD) of the communications network traffic can be measured using the Hurst parameter. There are various estimators of Hurst parameter which differ in reliability of their results. Getting reliable estimator can help to improve traffic characterization, performance modelling, planning and engineering of the real networks. This paper deals with the comparis...

Considering the time-series ARIMA(p,d, q) model and fuzzy regression model, this paper develops a fuzzy ARIMA (FARIMA) model and applies it to forecasting the exchange rate of NT dollars to US dollars. This model includes interval models with interval parameters and the possibility distribution of future values is provided by FARIMA. This model makes it possible for decision makers to forecast ...

This paper considers a class of semiparametric models being the sum of a nonparametric trend function g and a FARIMA-GARCH error process. Estimation of g( ), the th derivative of g, by local polynomial tting is investigated. The focus is on the derivation of the asymptotic normality of ĝ( ). At rst a central limit theorem based on martingale theory is developed and asymptotic normality of the s...

In this paper, we investigate the asymptotic properties of Le Cam’s one-step estimator for weak Fractionally AutoRegressive Integrated Moving-Average (FARIMA) models. For these models, noises are uncorrelated but neither necessarily independent nor martingale differences errors. We show under some regularity assumptions that is strongly consistent and asymptotically normal with same variance as...

In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficient ...

This paper investigates an influence of different SRD structures on a maximum delay value for queued LRD traffic with usage of an envelope analysis. A FARIMA process is used as a traffic model since it can model both SRD and LRD structures independently. A FGN process is used as a reference of LRD traffic due to its relative simplicity. A drop probability is computed as a function of a buffer s...