Academic scholars and industry professionals alike face the formidable challenge of staying informed about emerging trends and innovations in cloud computing. The expansive realm of cloud technology has been the catalyst for several transformative changes across industries, offering unparalleled opportunities for optimization and innovation. However, even seasoned experts may find themselves daunted by the intricate web of new technologies, including green cloud computing, edge computing, cryptography in the cloud, load balancing strategies, and cloud analytics insights. Emerging Trends in Cloud Computing: Analytics, Scalability, and Service Models provides academic scholars and industry professionals with a comprehensive exploration of these critical cloud computing topics and more. This invaluable resource provides clarity and insight, serving as a guiding beacon in the ever-evolving world of cloud technology. Whether you're seeking to understand the intricacies of cloud security solutions, the nuances of scalability in cloud computing, or the various service models in the cloud, this book empowers you to navigate this dynamic field with confidence and expertise.

"Big Data Analytics in the Cloud" is an illuminating exploration of the synergy between two transformative technologies-Big Data and Cloud Computing. In this comprehensive guide, readers embark on a journey through the data-driven landscape where massive datasets meet the scalability, flexibility, and power of cloud infrastructure. This book begins by unraveling the core concepts of Big Data, shedding light on its three defining characteristics: volume, velocity, and variety. Readers gain a deep understanding of the challenges organizations face when dealing with vast amounts of data and how traditional solutions often fall short in managing, processing, and deriving insights from it. Enter Cloud Computing, the dynamic and scalable solution to these challenges. The heart of "Big Data Analytics in the Cloud" lies in its exploration of how cloud technology reshapes the Big Data landscape. It delves into the intricacies of cloud-based data storage, processing, and analytics services, showcasing how they empower businesses to harness the full potential of their data. Real-world case studies and examples demonstrate how organizations leverage cloud-based Big Data analytics to gain a competitive edge, make data-driven decisions, and uncover valuable insights. The book provides a roadmap for designing and implementing Big Data analytics solutions in the cloud, covering key topics such as data ingestion, storage, transformation, analysis, and visualization. It discusses the advantages of cloud-native tools and platforms, including their cost-efficiency, scalability, and ease of use. Security and compliance are paramount in the world of data, and this guide devotes attention to how cloud providers address these concerns. It outlines best practices for securing data in the cloud, ensuring data privacy, and adhering to regulatory requirements. As technology evolves, so does this book. "Big Data Analytics in the Cloud" explores emerging trends and technologies in the field, such as serverless computing, AI and machine learning integration, and the intersection of Big Data with the Internet of Things (IoT). Whether you're a data scientist, a business executive seeking data-driven insights, or an IT professional responsible for implementing Big Data solutions, this book equips you with the knowledge and strategies needed to leverage the power of Big Data analytics in the cloud. It is your indispensable resource for navigating the intersection of two groundbreaking technologies and unlocking new possibilities in the data-driven era

This book comprehensively discusses the role of cloud computing in artificial intelligence‐based data‐driven systems and hybrid cloud computing for large data‐driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides Internet of Things‐based frameworks and advanced computing techniques to deal with online/virtual systems. This book: • Covers the aspects of security, authentication, and prediction for data‐driven systems in heterogeneous environments. • Provides data‐driven frameworks in combination with the Internet of Things, artificial intelligence, and computing to provide critical insights and decision‐making for real‐time problems. • Showcases deep learning‐based computer vision algorithms for enhanced pattern detection in different domains based on data‐centric approaches. • Examines the role of the Internet of Things and machine learning algorithms for data‐driven systems. • Highlights the applications of data‐driven systems and cloud computing in enhancing network performance. This book is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, and computer science engineering.

This book gives a complete overview of cloud computing: its importance, its trends, innovations, and its amalgamation with other technologies. Key Features: In-depth explanation of emerging technologies utilizing cloud computing Supplemented with visuals, flow charts, and diagrams Real-time examples included Caters to beginners, as well as advanced researchers, by explaining implications, innovations, issues, and challenges of cloud computing Highlights the need for cloud computing and the true benefits derived by its application and integration in emerging technologies Simple, easy language

Smart cities are experiencing a rapid evolution. The integration of technologies such as 5G, Internet of Things (IoT), Artificial Intelligence (AI), and blockchain has ushered in transformative applications, enhancing the quality of urban life. However, this evolution comes with its own challenges, most notably in security and privacy. Secure and Intelligent IoT-Enabled Smart Cities addresses these concerns, exploring theoretical frameworks and empirical research findings. The book embarks on the foundational elements of the Internet of Things, delving into the convergence of IoT and smart city applications, elucidating the layered architecture of IoT, and highlighting the security issues inherent in IoT-enabled Smart Cities. This book pinpoints the challenges smart city infrastructures face and offers innovative and pragmatic solutions to fortify their security. This book targets professionals and researchers immersed in the dynamic field of secure and intelligent environments within IoT-enabled smart city applications. It is a valuable resource for executives grappling with the strategic implications of emerging technologies in smart healthcare, smart parking, smart manufacturing, smart transportation, and beyond.

Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. Introduces data analysis techniques and cloud computing concepts Describes cloud-based models and systems for Big Data analytics Provides examples of the state-of-the-art in cloud data analysis Explains how to develop large-scale data mining applications on clouds Outlines the main research trends in the area of scalable Big Data analysis