David O. Loomis Illinois State University The explosive growth of the Internet has caught most industry experts off guard. While data communications was expected to be the "wave of the future," few industry observers foresaw how rapid the change in focus from voice communications towards data would be. Understanding the data communications revolution has become an urgent priority for many in the telecommunications industry. Demand analysis and forecasting are critical tools to understanding these trends for both Internet access and Internet backbone service. Businesses have led residential customers in the demand for data services, but residential demand is currently increasing exponentiall y. Even as business demand for data communications is becoming better understood, residential broadband access demand is still largely unexplored. Cable modems and ADSL appear to be the current residential broadband choices yet demand elasticities and econometric model-based forecasts for these services are not currently available. The responsiveness of customers to price and income changes and customer's perceptions of the tradeoff in product characteristics between cable modems and ADSL is largely unknown. Demand for Internet access is derived from the demand for applications which utilize this access; access is not demanded independent of its usage. Thus it is important to understand Internet applications in order to understand the demand for access.

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

This book presents original contributions on the theories and practices of emerging Internet, Data and Web technologies and their applications in businesses, engineering and academia. As a key feature, it addresses advances in the life-cycle exploitation of data generated by digital ecosystem technologies. The Internet has become the most proliferative platform for emerging large-scale computing paradigms. Among these, Data and Web technologies are two of the most prominent paradigms, manifesting in a variety of forms such as Data Centers, Cloud Computing, Mobile Cloud, Mobile Web Services, and so on. These technologies altogether create a digital ecosystem whose cornerstone is the data cycle, from capturing to processing, analysis and visualization. The need to investigate various research and development issues in this digital ecosystem has been made even more pressing by the ever-increasing demands of real-life applications, which are based on storing and processing large amounts of data. Given its scope, the book offers a valuable asset for all researchers, software developers, practitioners and students interested in the field of Data and Web technologies.

In the early 1990s, people predicted the death of privacy, an end to the current concept of 'property, ' a paperless society, 500 channels of high-definition interactive television, world peace, and the extinction of the human race after a takeover engineered by intelligent machines. Imagining the Internet zeroes in on predictions about the Internet's future and revisits past predictions--and how they turned out. It gives the history of communications in a nutshell, illustrating the serious impact of pervasive networks and how they will change our lives over the next century.

This book focuses on different algorithms and models related to AI, big data and IoT used for various domains. It enables the reader to have a broader and deeper understanding of several perspectives regarding the dynamics, challenges, and opportunities for sustainable development using artificial intelligence, big data and IoT. Applications of Artificial Intelligence, Big Data and Internet of Things (IoT) in Sustainable Development focuses on IT-based advancements in multidisciplinary fields such as healthcare, finance, bioinformatics, industrial automation, and environmental science. The authors discuss the key issues of security, management, and the realization of possible solutions to hurdles in sustainable development. The reader will master basic concepts and deep insights of various algorithms and models for various applications such as healthcare, finance, education, smart cities, smart cars, among others. Finally, the book will also examine the applications and implementation of big data IoT, AI strategies to facilitate the sustainable development goals set by the United Nations by 2030. This book is intended to help researchers, academics, and policymakers to analyze the challenges and future aspects for maintaining sustainable development through IoT, big data, and AI.