One of the major developments in the computing field has been cloud computing, which enables users to do complicated computations that local devices are unable to handle. The computing power and flexibility that have made the cloud so popular do not come without challenges. It is particularly challenging to decide which resources to use, even when they have the same configuration but different levels of performance because of the variable structure of the available resources. Cloud data centers can host millions of virtual machines, and where to locate these machines in the cloud is a difficult problem. Additionally, fulfilling optimization needs is a complex problem. Reliable and Intelligent Optimization in Multi-Layered Cloud Computing Architectures examines ways to meet these challenges. It discusses virtual machine placement techniques and task scheduling techniques that optimize resource utilization and minimize energy consumption of cloud data centers. Placement techniques presented can provide an optimal solution to the optimization problem using multiple objectives. The book focuses on basic design principles and analysis of virtual machine placement techniques and task allocation techniques. It also looks at virtual machine placement techniques that can improve quality-of-service (QoS) in service-oriented architecture (SOA) computing. The aims of virtual machine placement include minimizing energy usage, network traffic, economical cost, maximizing performance, and maximizing resource utilization. Other highlights of the book include: Improving QoS and resource efficiency Fault-tolerant and reliable resource optimization models A reactive fault tolerance method using checkpointing restart Cost and network-aware metaheuristics. Virtual machine scheduling and placement Electricity consumption in cloud data centers Written by leading experts and researchers, this book provides insights and techniques to those dedicated to improving cloud computing and its services.

Machine Learning and Models for Optimization in Cloud’s main aim is to meet the user requirement with high quality of service, least time for computation and high reliability. With increase in services migrating over cloud providers, the load over the cloud increases resulting in fault and various security failure in the system results in decreasing reliability. To fulfill this requirement cloud system uses intelligent metaheuristic and prediction algorithm to provide resources to the user in an efficient manner to manage the performance of the system and plan for upcoming requests. Intelligent algorithm helps the system to predict and find a suitable resource for a cloud environment in real time with least computational complexity taking into mind the system performance in under loaded and over loaded condition. This book discusses the future improvements and possible intelligent optimization models using artificial intelligence, deep learning techniques and other hybrid models to improve the performance of cloud. Various methods to enhance the directivity of cloud services have been presented which would enable cloud to provide better services, performance and quality of service to user. It talks about the next generation intelligent optimization and fault model to improve security and reliability of cloud. Key Features · Comprehensive introduction to cloud architecture and its service models. · Vulnerability and issues in cloud SAAS, PAAS and IAAS · Fundamental issues related to optimizing the performance in Cloud Computing using meta-heuristic, AI and ML models · Detailed study of optimization techniques, and fault management techniques in multi layered cloud. · Methods to improve reliability and fault in cloud using nature inspired algorithms and artificial neural network. · Advanced study of algorithms using artificial intelligence for optimization in cloud · Method for power efficient virtual machine placement using neural network in cloud · Method for task scheduling using metaheuristic algorithms. · A study of machine learning and deep learning inspired resource allocation algorithm for cloud in fault aware environment. This book aims to create a research interest & motivation for graduates degree or post-graduates. It aims to present a study on optimization algorithms in cloud for researchers to provide them with a glimpse of future of cloud computing in the era of artificial intelligence.

This book discusses various aspects of cloud computing, in which trust and fault-tolerance models are included in a multilayered, cloud architecture. The authors present a variety of trust and fault models used in the cloud, comparing them based on their functionality and the layer in the cloud to which they respond. Various methods are discussed that can improve the performance of cloud architectures, in terms of trust and fault-tolerance, while providing better performance and quality of service to user. The discussion also includes new algorithms that overcome drawbacks of existing methods, using a performance matrix for each functionality. This book provide readers with an overview of cloud computing and how trust and faults in cloud datacenters affects the performance and quality of service assured to the users. Discusses fundamental issues related to trust and fault-tolerance in Cloud Computing; Describes trust and fault management techniques in multi layered cloud architecture to improve security, reliability and performance of the system; Includes methods to enhance power efficiency and network efficiency, using trust and fault based resource allocation.

This book includes selected papers presented at International Conference on Computational Intelligence, Data Science,, and Cloud Computing (IEM-ICDC 2021), organized by the Department of Information Technology Institute of Engineering and Management, Kolkata, India, during December 22 – 24, 2021. It covers substantial new findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber-security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.

Elevate your expertise and gain holistic insights into cloud technology with a focus on smoothly transitioning from on-premises to the cloud Key Features Analyze cloud architecture in depth, including different layers, components, and design principles Explore various types of cloud services from AWS, Microsoft Azure, Google Cloud, Oracle Cloud Infrastructure, and more Implement best practices and understand the use of various cloud deployment tools Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the need for digital transformation and remote work surges, so does the demand for cloud computing. However, the complexity of cloud architecture and the abundance of vendors and tools can be overwhelming for businesses. This book addresses the need for skilled professionals capable of designing, building, and managing scalable and resilient cloud systems to navigate the complex landscape of cloud computing through practical tips and strategies. This comprehensive cloud computing guide offers the expertise and best practices for evaluating different cloud vendors and tools. The first part will help you gain a thorough understanding of cloud computing basics before delving deeper into cloud architecture, its design, and implementation. Armed with this expert insight, you'll be able to avoid costly mistakes, ensure that your cloud systems are secure and compliant, and build cloud systems that can adapt and grow with the business. By the end of this book, you’ll be proficient in leveraging different vendors and tools to build robust and secure cloud systems to achieve specific goals and meet business requirements.What you will learn Get to grips with the core concepts of cloud architecture and cost optimization Understand the different cloud deployment and service models Explore various cloud-related tools and technologies Discover cloud migration strategies and best practices Find out who the major cloud vendors are and what they offer Analyze the impact and future of cloud technology Who this book is for The book is for anyone interested in understanding cloud technology, including business leaders and IT professionals seeking insights into the benefits, challenges, and best practices of cloud computing. Those who are just starting to explore cloud technology, as well as those who are already using cloud technology and want to deepen their understanding to optimize usage, will find this resource especially useful.

FOG COMPUTING FOR INTELLIGENT CLOUD IOT SYSTEMS This book is a comprehensive guide on fog computing and how it facilitates computing, storage, and networking services Fog computing is a decentralized computing structure that connects data, devices, and the cloud. It is an extension of cloud computing and is an essential concept in IoT (Internet of Things), as it reduces the burden of processing in cloud computing. It brings intelligence and processing closer to where the data is created and transmitted to other sources. Fog computing has many benefits, such as reduced latency in processing data, better response time that helps the user’s experience, and security and privacy compliance that assures protecting the vital data in the cloud. It also reduces the cost of bandwidth, because the processing is achieved in the cloud, which reduces network bandwidth usage and increases efficiency as user devices share data in the local processing infrastructure rather than the cloud service. Fog computing has various applications across industries, such as agriculture and farming, the healthcare industry, smart cities, education, and entertainment. For example, in the agriculture industry, a very prominent example is the SWAMP project, which stands for Smart Water Management Platform. With fog computing’s help, SWAMP develops a precision-based smart irrigation system concept used in agriculture, minimizing water wastage. This book is divided into three sections. The first section studies fog computing and machine learning, covering fog computing architecture, application perspective, computational offloading in mobile cloud computing, intelligent Cloud-IoT systems, machine learning fundamentals, and data visualization. The second section focuses on applications and analytics, spanning various applications of fog computing, such as in healthcare, Industry 4.0, cancer cell detection systems, smart farming, and precision farming. This section also covers analytics in fog computing using big data and patient monitoring systems, and the emergence of fog computing concerning applications and potentialities in traditional and digital educational systems. Security aspects in fog computing through blockchain and IoT, and fine-grained access through attribute-based encryption for fog computing are also covered. Audience The book will be read by researchers and engineers in computer science, information technology, electronics, and communication specializing in machine learning, deep learning, the cyber world, IoT, and security systems.

Modern communication technologies such as 5G and 6G and the industrial internet of things have important attributes to meet the requirements of industries, and with the rapid development of the fourth industrial revolution and beyond, it is unavoidable that these will fulfill the necessary requirements of this important part of modernization. Opportunities and Challenges of Industrial IoT in 5G and 6G Networks ranges from the application of recently ratified communication standards, theoretical knowledge that provides tangible insight for understanding the principles of operation, design, implementation, and planning, to the outcomes from deployment of industrial projects. Covering topics such as 5G network programmability, industry policies, and optical networking technologies, this premier reference source is a valuable resource for computer scientists, IT specialists, industry consultants and professionals, business leaders, libraries, students, researchers, and academicians.

This book discusses harnessing the real power of cloud computing in optimization problems, presenting state-of-the-art computing paradigms, advances in applications, and challenges concerning both the theories and applications of cloud computing in optimization with a focus on diverse fields like the Internet of Things, fog-assisted cloud computing, and big data. In real life, many problems – ranging from social science to engineering sciences – can be identified as complex optimization problems. Very often these are intractable, and as a result researchers from industry as well as the academic community are concentrating their efforts on developing methods of addressing them. Further, the cloud computing paradigm plays a vital role in many areas of interest, like resource allocation, scheduling, energy management, virtualization, and security, and these areas are intertwined with many optimization problems. Using illustrations and figures, this book offers students and researchers a clear overview of the concepts and practices of cloud computing and its use in numerous complex optimization problems.

This symposium was born as a research forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; what we call Management Intelligent Systems (MiS). This volume presents the proceedings of these activities in a collection of contributions with many original approaches. They address diverse Management and Business areas of application such as decision support, segmentation of markets, CRM, product design, service personalization, organizational design, e-commerce, credit scoring, workplace integration, innovation management, business database analysis, workflow management, location of stores, etc. A wide variety of AI techniques have been applied to these areas such as multi-objective optimization and evolutionary algorithms, classification algorithms, ant algorithms, fuzzy rule-based systems, intelligent agents, Web mining, neural networks, Bayesian models, data warehousing, rough sets, etc. This volume also includes a track focused on the latest research on Intelligent Systems and Technology Enhanced Learning (iTEL), as well as its impacts for learners and institutions. It aims at bringing together researchers and developers from both the professional and the academic realms to present, discuss and debate the latest advances on intelligent systems and technology-enhanced learning The symposium was organized by the Soft Computing and Intelligent Information Systems Research Group (http://sci2s.ugr.es) of the University of Granada (Spain) and the Bioinformatics, Intelligent System and Educational Technology Research Group (http:// bisite.usal.es/) of the University of Salamanca (Spain). The present edition was held in Salamanca (Spain) on May 22–24, 2013.

The internet is making our daily life as digital as possible and this new era is called the Internet of Everything (IoE). Edge computing is an emerging data analytics concept that addresses the challenges associated with IoE. More specifically, edge computing facilitates data analysis at the edge of the network instead of interacting with cloud-based servers. Therefore, more and more devices need to be added in remote locations without any substantial monitoring strategy. This increased connectivity and the devices used for edge computing will create more room for cyber criminals to exploit the system’s vulnerabilities. Ensuring cyber security at the edge should not be an afterthought or a huge challenge. The devices used for edge computing are not designed with traditional IT hardware protocols. There are diverse-use cases in the context of edge computing and Internet of Things (IoT) in remote locations. However, the cyber security configuration and software updates are often overlooked when they are most needed to fight cyber crime and ensure data privacy. Therefore, the threat landscape in the context of edge computing becomes wider and far more challenging. There is a clear need for collaborative work throughout the entire value chain of the network. In this context, this book addresses the cyber security challenges associated with edge computing, which provides a bigger picture of the concepts, techniques, applications, and open research directions in this area. In addition, the book serves as a single source of reference for acquiring the knowledge on the technology, process and people involved in next generation computing and security. It will be a valuable aid for researchers, higher level students and professionals working in the area.