A study of self-similar traffic generation for ATM networks

This thesis discusses the efficient and accurate generation of self-similar traffic for ATM networks. ATM networks have been developed to carry multiple service categories. Since the traffic on a number of existing networks is bursty, much research focuses on how to capture the characteristics of traffic to reduce the impact of burstiness. Conventional traffic models do not represent the characteristics of burstiness well, but self-similar traffic models provide a closer approximation. Self-similar traffic models have two fundamental properties, long-range dependence and infinite variance, which have been found in a large number of measurements of real traffic. Therefore, generation of self-similar traffic is vital for the accurate simulation of ATM networks. The main starting point for self-similar traffic generation is the production of fractional Brownian motion (FBM) or fractional Gaussian noise (FGN). In this thesis six algorithms are brought together so that their efficiency and accuracy can be assessed. It is shown that the discrete FGN (dPGN) algorithm and the Weierstrass-Mandelbrot (WM) function are the best in terms of accuracy while the random midpoint displacement (RMD) algorithm, successive random addition (SRA) algorithm, and the WM function are superior in terms of efficiency. Three hybrid approaches are suggested to overcome the inefficiency or inaccuracy of the six algorithms. The combination of the dFGN and RMD algorithm was found to be the best in that it can generate accurate samples efficiently and on-the-fly. After generating FBM sample traces, a further transformation needs to be conducted with either the marginal distribution model or the storage model to produce self-similar traffic. The storage model is a better transformation because it provides a more rigorous mathematical derivation and interpretation of physical meaning. The suitability of using selected Hurst estimators, the rescaled adjusted range (R/S) statistic, the variance-time (VT) plot, and Whittle's approximate maximum likelihood estimator (MLE), is also covered. Whittle's MLE is the better estimator, the R/S statistic can only be used as a reference, and the VT plot might misrepresent the actual Hurst value. An improved method for the generation of self-similar traces and their conversion to traffic has been proposed. This, combined with the identification of reliable methods for the estimators of the Hurst parameter, significantly advances the use of self-similar traffic models in ATM network simulation

Health, physical activity and fitness monitoring within the secondary physical education curriculum in England

The aims of this study are three-fold: to review the worldwide literature on monitoring the health, physical activity and fitness of young people; to determine the purpose and prevalence of the monitoring of young people's health, physical activity and fitness within secondary PE school curricula in England and to explore the factors affecting teachers' views of and approaches to such monitoring; and to propose recommendations for monitoring health, physical activity and fitness within secondary school PE curricula in England which may have relevance and applicability to the Taiwanese context. [Continues.

Design of nearest neighbor classifiers: multi-objective approach

AbstractThe goal of designing optimal nearest neighbor classifiers is to maximize classification accuracy while minimizing the sizes of both reference and feature sets. A usual way is to adaptively weight the three objectives as an objective function and then use a single-objective optimization method for achieving this goal. This paper proposes a multi-objective approach to cope with the weight tuning problem for practitioners. A novel intelligent multi-objective evolutionary algorithm IMOEA is utilized to simultaneously edit compact reference and feature sets for nearest neighbor classification. Three comparison studies are designed to evaluate performance of the proposed approach. It is shown empirically that the IMOEA-designed classifiers have high classification accuracy and small sizes of reference and feature sets. Moreover, IMOEA can provide a set of good solutions for practitioners to choose from in a single run. The simulation results indicate that the IMOEA-based approach is an expedient method to design nearest neighbor classifiers, compared with an existing single-objective approach

Antidumping Petition: To File or Not To File

Given the “normal value†of a product as common knowledge in an import-competing market, the profitability of a home firm in filing an antidumping (AD) petition against its foreign rival is shown to depend on the marginal cost differential between the home and foreign firms. When the marginal cost differential is “significantly large,†the home firm's ability to put the foreign firm at the risk of an AD violation is limited. But when the marginal cost differential is “significantly small,†the home firm is able to increase its output and lower the price of the product below its normal value, putting the foreign firm in the situation of an illegal dumping. One interesting implication is that, relative to the case without an AD law, the home firm has a stronger incentive to undertake cost-reducing activities (e.g., R&D investment or the adoption of a more efficient technology) under the law.antidumping laws, antidumping duties, dumping margins

The Impact of ECN on the Trading Structure of Taiwan\u27s Securities Market

Along with the booming of internet, many enterprises have modified their business models accordingly, which then has influenced the trend and direction of many industries. In the securities market, investors could utilize internet to obtain order information more easily and completely. Especially, with the easy access of foreign securities information through internet, investments transactions are becoming globalized too. Traditional trading support no longer satisfies investors’ requirements. That has contributed to the global rise of electronic communications networks (ECNs). These new trading platforms make the competition among exchanges more severe. With the gradual opening of Taiwan’s financial market, the approaching of these new players becomes inevitable. We study the impact of ECN on the trading structure of Taiwan’s securities market, based on the trading contents, trading methods, and trading support requirements. We first analyze the impact of ECN on the trading structure of United States securities market. Current trading structure of Taiwan’s securities market is then analyzed for stocks, bonds, and futures separately. We also develop an experimental ECN with the negotiation mechanism. The system is then tested by several trading experts. Their answers to our survey are summarized as our conclusion