Modelado y simulación de sistemas de gran escala

Las simulaciones computacionales permiten entender los elementos y patrones que pueden alterar un sistema y puede ser utilizada para estudiar sistemas complejos, incluyendo aquellos que son analíticamente intratables. La simulación también es utilizada cuando no se tienen los recursos computacionales disponibles. En estos casos se puede estimar diferentes parámetros como la escalabilidad de los sistemas, a medida que se simula el aumento del número de recursos asignados. En otras palabras, utilizando técnicas de modelado y simulaciones eficientes es posible diseñar, desarrollar y evaluar sistemas de gran escala. En este trabajo, se presentan los objetivos, trabajo realizado y desafíos que aborda el grupo de investigación de la Universidad Nacional de San Luis, para abordar los temas que involucra el diseño de simulaciones de sistemas complejos y de gran escala para procesar grandes volúmenes de datos e información.Eje: Procesamiento Distribuido y Paralelo.Red de Universidades con Carreras en Informática (RedUNCI

Modelado y simulación de sistemas de gran escala

Las simulaciones computacionales permiten entender los elementos y patrones que pueden alterar un sistema y puede ser utilizada para estudiar sistemas complejos, incluyendo aquellos que son analíticamente intratables. La simulación también es utilizada cuando no se tienen los recursos computacionales disponibles. En estos casos se puede estimar diferentes parámetros como la escalabilidad de los sistemas, a medida que se simula el aumento del número de recursos asignados. En otras palabras, utilizando técnicas de modelado y simulaciones eficientes es posible diseñar, desarrollar y evaluar sistemas de gran escala. En este trabajo, se presentan los objetivos, trabajo realizado y desafíos que aborda el grupo de investigación de la Universidad Nacional de San Luis, para abordar los temas que involucra el diseño de simulaciones de sistemas complejos y de gran escala para procesar grandes volúmenes de datos e información.Eje: Procesamiento Distribuido y Paralelo.Red de Universidades con Carreras en Informática (RedUNCI

Modelado y simulación de sistemas de gran escala

Las simulaciones computacionales permiten entender los elementos y patrones que pueden alterar un sistema y puede ser utilizada para estudiar sistemas complejos, incluyendo aquellos que son analíticamente intratables. La simulación también es utilizada cuando no se tienen los recursos computacionales disponibles. En estos casos se puede estimar diferentes parámetros como la escalabilidad de los sistemas, a medida que se simula el aumento del número de recursos asignados. En otras palabras, utilizando técnicas de modelado y simulaciones eficientes es posible diseñar, desarrollar y evaluar sistemas de gran escala. En este trabajo, se presentan los objetivos, trabajo realizado y desafíos que aborda el grupo de investigación de la Universidad Nacional de San Luis, para abordar los temas que involucra el diseño de simulaciones de sistemas complejos y de gran escala para procesar grandes volúmenes de datos e información.Eje: Procesamiento Distribuido y Paralelo.Red de Universidades con Carreras en Informática (RedUNCI

A survey of AI in operations management from 2005 to 2009

Purpose: the use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the ten-year period 1995-2004. Like the previous survey, it uses Elsevier’s Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case-based reasoning (CBR), fuzzy logic (FL), knowledge-Based systems (KBS), data mining, and hybrid AI in the four application areas are identified. Findings: the survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004 (Kobbacy et al. 2007). Like the previous survey, it uses the Elsevier’s ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings: The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research

Telecommunication Economics

This book constitutes a collaborative and selected documentation of the scientific outcome of the European COST Action IS0605 Econ@Tel "A Telecommunications Economics COST Network" which run from October 2007 to October 2011. Involving experts from around 20 European countries, the goal of Econ@Tel was to develop a strategic research and training network among key people and organizations in order to enhance Europe's competence in the field of telecommunications economics. Reflecting the organization of the COST Action IS0605 Econ@Tel in working groups the following four major research areas are addressed: - evolution and regulation of communication ecosystems; - social and policy implications of communication technologies; - economics and governance of future networks; - future networks management architectures and mechanisms

Security Technologies and Methods for Advanced Cyber Threat Intelligence, Detection and Mitigation

The rapid growth of the Internet interconnectivity and complexity of communication systems has led us to a significant growth of cyberattacks globally often with severe and disastrous consequences. The swift development of more innovative and effective (cyber)security solutions and approaches are vital which can detect, mitigate and prevent from these serious consequences. Cybersecurity is gaining momentum and is scaling up in very many areas. This book builds on the experience of the Cyber-Trust EU project’s methods, use cases, technology development, testing and validation and extends into a broader science, lead IT industry market and applied research with practical cases. It offers new perspectives on advanced (cyber) security innovation (eco) systems covering key different perspectives. The book provides insights on new security technologies and methods for advanced cyber threat intelligence, detection and mitigation. We cover topics such as cyber-security and AI, cyber-threat intelligence, digital forensics, moving target defense, intrusion detection systems, post-quantum security, privacy and data protection, security visualization, smart contracts security, software security, blockchain, security architectures, system and data integrity, trust management systems, distributed systems security, dynamic risk management, privacy and ethics

Security Technologies and Methods for Advanced Cyber Threat Intelligence, Detection and Mitigation

The rapid growth of the Internet interconnectivity and complexity of communication systems has led us to a significant growth of cyberattacks globally often with severe and disastrous consequences. The swift development of more innovative and effective (cyber)security solutions and approaches are vital which can detect, mitigate and prevent from these serious consequences. Cybersecurity is gaining momentum and is scaling up in very many areas. This book builds on the experience of the Cyber-Trust EU project’s methods, use cases, technology development, testing and validation and extends into a broader science, lead IT industry market and applied research with practical cases. It offers new perspectives on advanced (cyber) security innovation (eco) systems covering key different perspectives. The book provides insights on new security technologies and methods for advanced cyber threat intelligence, detection and mitigation. We cover topics such as cyber-security and AI, cyber-threat intelligence, digital forensics, moving target defense, intrusion detection systems, post-quantum security, privacy and data protection, security visualization, smart contracts security, software security, blockchain, security architectures, system and data integrity, trust management systems, distributed systems security, dynamic risk management, privacy and ethics

Telecommunication Economics

This book constitutes a collaborative and selected documentation of the scientific outcome of the European COST Action IS0605 Econ@Tel "A Telecommunications Economics COST Network" which run from October 2007 to October 2011. Involving experts from around 20 European countries, the goal of Econ@Tel was to develop a strategic research and training network among key people and organizations in order to enhance Europe's competence in the field of telecommunications economics. Reflecting the organization of the COST Action IS0605 Econ@Tel in working groups the following four major research areas are addressed: - evolution and regulation of communication ecosystems; - social and policy implications of communication technologies; - economics and governance of future networks; - future networks management architectures and mechanisms