Study of consensus protocols and improvement of the Federated Byzantine Agreement (FBA) algorithm

At a present time, it has been proven that blockchain technology has influenced to a great extent the way of human interaction in a digital world. The operation of the blockchain systems allows the peers to implement digital transactions in a Peer to Peer (P2P) network in a direct way without the need of third parties. Each blockchain determines different rules for the record of the transactions in the ledger. The transactions are inserted in blocks and each one, in turn, is appended to the chain (ledger) based on different consensus algorithms. Once blocks have been inserted in the chain, the consensus has been reached and the blocks with corresponding transactions are considered immutable. This thesis analyses the main features of the blockchain and how the consensus can be achieved through the different kinds of consensus algorithms. In addition, a detailed reference for Stellar and Federated Byzantine Agreement (FBA) consensus protocols is made in order to explain these algorithms, their limitations as well as their improvement. The development of a reputation mechanism is necessary to the improvement of above algorithms

A Case Study Approach for Managing Risks & Challenges When Expanding to Emerging Markets

Globalization created new opportunities and many companies decide to expand to take advantage of these opportunities to improve their competitiveness. The present study, using a case study methodology, examines the expansion of three large companies (IKEA, Coca Cola and Kellogg's) in emerging markets. Through a critical literature review and review of corporate reports, the study analyzes companies’ adopted strategies and practices, influential factors and risks when expanding abroad, providing the rationale behind their strategic choices. The study findings, applying theory into practice, indicate the factors and practices that are important to be considered by companies operating in a foreign environment in order to address business risks, and concludes that in order to be successful they have to incorporate into their strategy effective risk management policies to mitigate risks and turn challenges into opportunities. The study bridges risk management and strategy development

A Simulation Study on the Performance of Extreme-Value Index Estimators and Proposed Robustifying Modifications

The key issue of extreme-value theory is the estimation of a parameter γ, known as extreme value index. In this paper we review several extreme-value index estimators, ranging from the oldest ones to the most recent developments. Moreover, a smoothing procedure of these estimators are presented. A simulation study is conducted in order to compare the behaviour of the estimators and their smoothed alternatives. Maybe the most prominent results of this study is that no uniformly best estimator exists and that the behaviour of estimators depends on the value of the parameter γ itself.Extreme value index, Semi-parametric estimation, Smoothing modification

Extreme Value Analysis of Teletraffic Data

An empirically verified characteristic of the expanding area of Internet is the longtailness of phenomena such as cpu time to complete a job, call holding times, files lengths requested, inter-arrival times and so on. Extreme values of the above quantities are liable to cause problems to the efficient operation of the network and call for effective design and management. Extreme-value analysis is an area of statistical analysis particularly concerned with the systematic study of extremes, providing useful insight to fields where extreme values are probable to occur and have detrimental effects, as is the case of teletraffics. In this paper we illustrate the main elements of this analysis and proceed to a detailed application of extreme-value analysis concepts to a specific teletraffic data set. This analysis verifies, too, the existence of long tails in the data.Teletraffic engineering, Long tails, Extreme-value index, Smoothing procedures

Extreme Value Index Estimators and Smoothing Alternatives: A Critical Review

Extreme-value theory and corresponding analysis is an issue extensively applied in many different fields. The central point of this theory is the estimation of a parameter γ, known as the extreme-value index. In this paper we review several extreme-value index estimators, ranging from the oldest ones to the most recent developments. Moreover, some smoothing and robustifying procedures of these estimators are presented.Extreme value index, Semi-parametric estimation, Smoothing modification

Extreme Value Index Estimators and Smoothing Alternatives: Review and Simulation Comparison

Extreme-value theory and corresponding analysis is an issue extensively applied in many different fields. The central point of this theory is the estimation of a parameter γ, known as extreme-value index. In this paper we review several extreme-value index estimators, ranging from the oldest ones to the most recent developments. Moreover, some smoothing and robustifying procedures of these estimators are presented. A simulation study is conducted in order to compare the behaviour of the estimators and their smoothed alternatives. Maybe, the most prominent result of this study is that no uniformly best estimator exists and that the behaviour of estimators depends on the value of the parameter γ itselfExtreme value index, Semi-parametric estimation, Smoothing modification

Application of a maximum likelihood processor to acoustic backscatter for the estimation of seafloor roughness parameters

Maximum likelihood (ML) estimation is used to extract seafloor roughness parameters from records of acoustic backscatter. The method relies on the Helmholtz–Kirchhoff approximation under the assumption of a power‐law roughness spectrum and on the statistical modeling of bottom reverberation. The result is a globally optimum, highly automated technique that is a useful tool in the context of seafloor classification via remote acoustic sensing. The general geometry of the Sea Beam bathymetric system is incorporated into the design of the ML processor in order to make it applicable to real acoustic data collected by this system. The processor is initially tested on simulated backscatter data and is shown to be very effective in estimating the seafloor parameters of interest. The simulated data are also used to study the effect of data averaging and normalization in the absence of system calibration information. The same estimation procedure is applied to real data collected over two central North Pacific seamounts, Horizon Guyot and Magellan Rise. The Horizon Guyot results are very close to estimates obtained through a curve‐fitting procedure presented by de Moustier and Alexandrou [J. Acoust. Soc. Am. 90, 522–531 (1991)]. In the case of Magellan Rise, discrepancies are observed between the results of ML estimation and curve fitting