This book is written for the first security hire in an organization, either an individual moving into this role from within the organization or hired into the role. More and more, organizations are realizing that information security requires a dedicated team with leadership distinct from information technology, and often the people who are placed into those positions have no idea where to start or how to prioritize. There are many issues competing for their attention, standards that say do this or do that, laws, regulations, customer demands, and no guidance on what is actually effective. This book offers guidance on approaches that work for how you prioritize and build a comprehensive information security program that protects your organization. While most books targeted at information security professionals explore specific subjects with deep expertise, this book explores the depth and breadth of the field. Instead of exploring a technology such as cloud security or a technique such as risk analysis, this book places those into the larger context of how to meet an organization's needs, how to prioritize, and what success looks like. Guides to the maturation of practice are offered, along with pointers for each topic on where to go for an in-depth exploration of each topic. Unlike more typical books on information security that advocate a single perspective, this book explores competing perspectives with an eye to providing the pros and cons of the different approaches and the implications of choices on implementation and on maturity, as often a choice on an approach needs to change as an organization grows and matures.

The opportunistic network is an emerging and recent area of research. To make this research area more adaptable for practical and industrial use, there is a need to further investigate several research challenges in all aspects of opportunistic networks. Therefore, Opportunistic Networks: Fundamentals, Applications and Emerging Trends provides theoretical, algorithmic, simulation, and implementation-based research developments related to fundamentals, applications, and emerging research trends in opportunistic networks. The book follows a theoretical approach to describe fundamentals to beginners and incorporates a practical approach depicting the implementation of real-life applications to intermediate and advanced readers. This book is beneficial for academicians, researchers, developers, and engineers who work in or are interested in the fields related to opportunistic networks, delay tolerant networks, and intermittently connected ad hoc networks. This book also serves as a reference book for graduate and postgraduate courses in computer science, computer engineering, and information technology streams.

Fueled by ubiquitous computing ambitions, the edge is at the center of confluence of many emergent technological trends such as hardware-rooted trust and code integrity, 5G, data privacy and sovereignty, blockchains and distributed ledgers, ubiquitous sensors and drones, autonomous systems and real-time stream processing. Hardware and software pattern maturity have reached a tipping point so that scenarios like smart homes, smart factories, smart buildings, smart cities, smart grids, smart cars, smart highways are in reach of becoming a reality. While there is a great desire to bring born-in-the-cloud patterns and technologies such as zero-downtime software and hardware updates/upgrades to the edge, developers and operators alike face a unique set of challenges due to environmental differences such as resource constraints, network availability and heterogeneity of the environment. The first part of the book discusses various edge computing patterns which the authors have observed, and the reasons why these observations have led them to believe that there is a need for a new architectural paradigm for the new problem domain. Edge computing is examined from the app designer and architect's perspectives. When they design for edge computing, they need a new design language that can help them to express how capabilities are discovered, delivered and consumed, and how to leverage these capabilities regardless of location and network connectivity. Capability-Oriented Architecture is designed to provide a framework for all of these. This book is for everyone who is interested in understanding what ubiquitous and edge computing means, why it is growing in importance and its opportunities to you as a technologist or decision maker. The book covers the broad spectrum of edge environments, their challenges and how you can address them as a developer or an operator. The book concludes with an introduction to a new architectural paradigm called capability-based architecture, which takes into consideration the capabilities provided by an edge environment. .

This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit. By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people's behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them. It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.

Reviews IoT software architecture and middleware, data processing and management, security, privacy and reliability, architectures, protocols, technologies, algorithms, and smart objects, sensors, and actuators Explores IoT as it applies to energy, including energy efficiency and management, intelligent energy management, smart energy through blockchain and energy-efficient/aware routing/scheduling challenges and issues Examines IoT as it applies to healthcare including biomedical image and signal analysis, and disease prediction and diagnosis Examines IoT as it applies to smart industry including architecture, blockchain, and Industry 4.0 Discusses different ways to create a better IoT network or IoT platform

A heterogeneous network is a network which connects computers and other devices with different operating systems, protocols, or access technologies. By definition, managing heterogenous networks is more difficult that homogenous networks. Confidentiality, integrity, availability (CIA) remain the foundation of security. This book sheds light upon security threats, defenses, and remediation on various networking and data processing domains, including wired networks, wireless networks, mobile ad-hoc networks, wireless sensor networks, and social networks through the prisms of confidentiality, integrity, availability, authentication, and access control. The book is broken into different chapters that explore central subjects and themes in the development of the heterogenous networks we see today. The chapters look at: Access control methods in cloud-enabled Internet of Things Secure routing algorithms for mobile ad-hoc networks Building security trust in mobile ad-hoc networks using soft computing methods The use and development of Blockchain technology, with a particular focus on the nonce-free hash generation in Blockchain Password authentication and keystroke biometrics Health care data analytics over Big Data Bluetooth: and its open issues for managing security services in heterogenous networks Managing Security Services in Heterogenous Networks will be a valuable resource for a whole host of undergraduate and postgraduate students studying related topics, as well as career professionals who have to effectively manage heterogenous networks in the workplace.

Provides a structured look, at the unique characteristic for smart sensor networks to resolving the issues of many real-world applications in a broad range of areas such as Smart Healthcare, Engineering, Scientific Research, Social Media, Industrial Automation and more Offers a systematic look at the unique characteristics of AI based wireless sensor networks through their usage in a broad range of areas Delivers recent trends and core concepts in both analytics and application in smart sensor networks using AI Explores the development and application of AI and evolutionary computing as applied to wireless sensor networks Focuses on stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation result and an application-oriented approach.

Blockchain is the popular name given to the exciting, evolving world of distributed ledger technology (DLT). Blockchains offer equitable and secure access to data, as well as transparency and immutability. Organisations can decide to use blockchain to upgrade whatever ledgers they are currently deploying (for example, relational databases, spreadsheets and cumbersome operating models) for their data and technology stack in terms of books and records, transactions, storage, production services and in many other areas. This book describes the applied use of blockchain technology in the enterprise world. Written by two expert practitioners in the field, the book is in two main parts: (1) an introduction to the history of, and a critical context explainer about, the emergence of blockchain written in natural language and providing a tour of the features, functionality and challenges of blockchain and DLT; and (2) a series of six applied organisational use cases in (i) trade finance, (ii) healthcare, (iii) retail savings & investments, (iv) real estate, (v) central bank digital currencies (CBDC) and (vi) fund management that offer the reader a straightforward, easy-to-read comparison between 'old world' technology (such as platforms, people and processes) versus what blockchain ledgers offer to enterprises and organisations in terms of improved efficiency, performance, security and access to business data. Blockchain is sometimes tainted by association to Bitcoin, Onecoin and others. But as cryptocurrencies and stock markets continue to rise and fall with volatility and the world economy emerges changed by coronavirus, working from home and the threat of inflation, many enterprises, organisations and governments are looking again at the powerful features of blockchain and wondering how DLT may help them adapt. This book is an ideal introduction to the practical and applied nature of blockchain and DLT solutions for business executives, business students, managers, C-suite senior leaders, software architects and policy makers and sets out, clearly and professionally, the benefits and challenges of the actual business applications of blockchain.

Provides insight into the skill set that requires leveraging strength to move further to act as a good data analyst Discusses how big data along with deep learning holds the potential to significantly increase data understanding and in turn, helps to make decisions Covers the numerous potential applications in healthcare, education, communications, media, and the entertainment industry Offers innovative platforms for integrating big data and deep learning Presents issues related to adequate data storage, sematic indexing, data tagging, and fast information retrieval from big data

A Practical Introduction to Enterprise Network and Security Management, Second Edition, provides a balanced understanding of introductory and advanced subjects in both computer networking and cybersecurity. Although much of the focus is on technical concepts, managerial issues related to enterprise network and security planning and design are explained from a practitioner's perspective. Because of the critical importance of cybersecurity in today's enterprise networks, security-related issues are explained throughout the book, and four chapters are dedicated to fundamental knowledge. Challenging concepts are explained so readers can follow through with careful reading. This book is written for those who are self-studying or studying information systems or computer science in a classroom setting. If used for a course, it has enough material for a semester or a quarter. FEATURES Provides both theoretical and practical hands-on knowledge and learning experiences for computer networking and cybersecurity Offers a solid knowledge base for those preparing for certificate tests, such as CompTIA and CISSP Takes advantage of actual cases, examples, industry products, and services so students can relate concepts and theories to practice Explains subjects in a systematic and practical manner to facilitate understanding Includes practical exercise questions that can be individual or group assignments within or without a classroom Contains several information-rich screenshots, figures, and tables carefully constructed to solidify concepts and enhance visual learning The text is designed for students studying information systems or computer science for the first time. As a textbook, this book includes hands-on assignments based on the Packet Tracer program, an excellent network design and simulation tool from Cisco. Instructor materials also are provided, including PowerPoint slides, solutions for exercise questions, and additional chapter questions from which to build tests.

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy. The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.

The book is based on the best papers of IEEE IRI 2018 and IEEE FMI 2018, Salt Lake City, July, 2018. They have been enhanced and modified suitably for publication. The book comprises recent works covering several aspects of reuse in intelligent systems - including Scientific Theory and Technology-Based Applications. New data analytic algorithms, technologies, and tools are sought to be able to manage, integrate, and utilize large amounts of data despite hardware, software, and/or bandwidth constraints; to construct models yielding important data insights, and to create visualizations to aid in presenting and understanding the data. Furthermore, it addresses the representation, cleansing, generalization, validation, and reasoning strategies for the scientifically-sound and cost-effective advancement of all kinds of intelligent systems - including all software and hardware aspects. The book addresses problems such as, how to optimally select the information/data sets for reuse and how to optimize the integration of existing information/knowledge with new, developing information/knowledge sources!

Google's Programmable Search Engines (PSEs, previously called Custom Search Engines) provide search opportunities that are unavailable with any other tool. PSEs have advanced settings and search operators that are not supported by "regular" Google. With PSEs, it is possible to perform filtered searches within parts of the web as if they were databases! While lots of professionals use existing PSEs to source for talent or with other research goals, few people have experience creating them. Even fewer know about powerful PSE-only search operators. The main reason PSEs are not as popular as they should be is that it is not easy to get educated on PSE creation. There is little information online and no books (other than this one) on the subject. Even less info is available on the "structured" operators that allow for filtered searches. The first of its kind, this book hopes to popularize these fun and powerful tools so that many more people can include PSEs in their work. Key Features: A detailed introduction to creating PSEs, including info absent in Google's help A "hack" for creating PSEs that look for profiles in seconds An introduction to advanced PSE-only search operators allowed to perform filtered searches of parts of the web A "hack" for expanding Google's search limits to 500 terms Use cases, examples, and approaches that would be educational for those doing online research This book will be of interest to researchers, OSINT specialists, investigative journalists, Competitive Intelligence people, recruiters, and Sourcers, to name a few categories, and to the general public interested in how to search better.

The book provides knowledge in the Building Information Model (BIM)-enabled cognitive computing methods for smart built environment involving cognitive network capabilities for smart buildings, integrating Augmented Reality/Mixed Reality in cognitive building concepts, cognitive Internet of Things (CIoT) for smart cities, Artificial Intelligence applications for cognitive cities, and cognitive smart cities using big data and machine learning. It focuses on the potential, requirements and implementation of CIoT paradigm to buildings, Artificial Intelligence techniques, reasoning, and Augmented Reality/Mixed Reality in cognitive building concepts, the concept of cognitive smart cities in its complexity, heterogeneity, and scope, and the challenge of utilizing the big data generated by smart cities from a machine learning perspective. The book comprises BIM-based and data-analytic research on cognitive IoT for smart buildings and cognitive cities using big data and machine learning as complex and dynamic systems. It presents applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the motivating physical and informational settings. It reviews ongoing development of BIM-based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to cognitive systems that will advance different aspects of future cognitive cities. The book also analyses the required material to inform pertinent research communities of the state-of-the-art research and the latest development in the area of cognitive smart cities development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of CIoT based on big data analytics and context-aware computing.

New computational design tools have evolved rapidly and been increasingly applied in the field of design in recent years, complimenting and even replacing the traditional design media and approaches. Design as both the process and product are changing due to the emergence and adoption of these new technologies. Understanding and assessing the impact of these new computational design environments on design and designers is important for advancing design in the contemporary context. Do these new computational environments support or hinder design creativity? How do those tools facilitate designers' thinking? Such knowledge is also important for the future development of design technologies. Research shows that design is never a mysterious non-understandable process, for example, one general view is that design process shares a common analysis-synthesis-evaluation model, during which designers interact between design problem and solution spaces. Understanding designers' thinking in different environments is the key to design research, education and practice. This book focuses on emerging computational design environments, whose impact on design and designers have not been comprehensively and systematically studied. It comprises three parts. The history and recent developments of computational design technologies are introduced in Part I. The main categories of technologies cover from computer-aided drafting and modelling tools, to visual programming and scripting tools for algorithmic design, to advanced interfaces and platforms for interactions between designers, between designers and computers, and between the virtual environment and the physical reality. To critically explore design thinking, especially in these new computational design environments, formal approaches to studying design thinking and design cognition are introduced and compared in Part II, drawing on literature and studies from the 70s to the current era. Part III concludes the book by exploring the impact of different computational design technologies on design and designers, using a series of case studies conducted by the author team building on their close collaboration over the past five years. The book offers new insights into designers' thinking in the rapidly evolving computational design environments, which have not been critically and systematically studied and reported in the current literature. The book is meant for design researchers, educators and students, professional practitioners and consultants, as well as people who are interested in computational design in general.

As more and more devices become interconnected through the Internet of Things (IoT), there is an even greater need for this book,which explains the technology, the internetworking, and applications that are making IoT an everyday reality. The book begins with a discussion of IoT "ecosystems" and the technology that enables them, which includes: Wireless Infrastructure and Service Discovery Protocols Integration Technologies and Tools Application and Analytics Enablement Platforms A chapter on next-generation cloud infrastructure explains hosting IoT platforms and applications. A chapter on data analytics throws light on IoT data collection, storage, translation, real-time processing, mining, and analysis, all of which can yield actionable insights from the data collected by IoT applications. There is also a chapter on edge/fog computing. The second half of the book presents various IoT ecosystem use cases. One chapter discusses smart airports and highlights the role of IoT integration. It explains how mobile devices, mobile technology, wearables, RFID sensors, and beacons work together as the core technologies of a smart airport. Integrating these components into the airport ecosystem is examined in detail, and use cases and real-life examples illustrate this IoT ecosystem in operation. Another in-depth look is on envisioning smart healthcare systems in a connected world. This chapter focuses on the requirements, promising applications, and roles of cloud computing and data analytics. The book also examines smart homes, smart cities, and smart governments. The book concludes with a chapter on IoT security and privacy. This chapter examines the emerging security and privacy requirements of IoT environments. The security issues and an assortment of surmounting techniques and best practices are also discussed in this chapter.

The emergence of highly promising and potent technologies has enabled the transition of ordinary objects into smart artifacts-providing wider connectivity of digitized entities that can facilitate the building of connected cities. This book provides readers with a solid foundation on the latest technologies and tools required to develop and enhance smart cities around the world. The book begins by examining the rise of the cloud as the fundamental technology for establishing and sustaining smart cities and enterprises. Explaining the principal technologies and platform solutions for implementing intelligent cities, the book details the role of various technologies, standards, protocols, and tools in establishing flexible homes and the buildings of the future. Examines IT platforms and tools from various product vendors Considers service-oriented architecture and event-driven architecture for smart city applications Explains how to leverage big data analytics for smart city enhancement and improved decision making Includes case studies of intelligent cities, smart homes, buildings, transports, healthcare systems, and airports The authors explore the convergence of cloud computing and enterprise architecture and present valuable information on next-generation cloud computing. They also cover the various architectural types, including enterprise-scale integration, security, management, and governance. The book concludes by explaining the various security requirements of intelligent cities as well as the threats and vulnerabilities of the various components that form the basis of the intelligent city framework, including cloud, big data, Internet of Things, and mobile technologies.

Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor - Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.

In practice, many different people with backgrounds in many different disciplines contribute to the design of an enterprise. Anyone who makes decisions to change the current enterprise to achieve some preferred structure is considered a designer. What is problematic is how to use the knowledge of separate aspects of the enterprise to achieve a globally optimized enterprise. The synthesis of knowledge from many disciplines to design an enterprise defines the field of enterprise engineering. Because enterprise systems are exceedingly complex, encompassing many independent domains of study, students must first be taught how to think about enterprise systems. Specifically written for advanced and intermediate courses and modules, Design of Enterprise Systems: Theory, Architecture, and Methods takes a system-theoretical perspective of the enterprise. It describes a systematic approach, called the enterprise design method, to design the enterprise. The design method demonstrates the principles, models, methods, and tools needed to design enterprise systems. The author uses the enterprise system design methodology to organize the chapters to mimic the completion of an actual project. Thus, the book details the enterprise engineering process from initial conceptualization of an enterprise to its final design. Pedagogical tools available include: For instructors: PowerPoint (R) slides for each chapter Project case studies that can be assigned as long-term projects to accompany the text Quiz questions for each chapter Business Process Analyzer software available for download For students: Templates, checklists, forms, and models to support enterprise engineering activities The book fills a need for greater design content in engineering curricula by describing how to design enterprise systems. Inclusion of design is also critical for business students, since they must realize the import their decisions may have on the long-term design of the enterprises they work with. The book's practical focus and project-based approach coupled with the pedagogical tools gives students the knowledge and skills they need to lead enterprise engineering projects.

Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book: Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions. Points to the solutions provided by machine learning to optimize the grids within a smart city set-up. Discusses relevant IoE design principles and architecture. Helps to automate various services in smart cities for energy management. Includes case studies to show the effectiveness of the discussed schemes.

Cloud Data Center Network Architectures and Technologies has been written with the support of Huawei's vast technical knowledge and experience in the data center network (DCN) field, as well as its understanding of customer service requirements. This book describes in detail the architecture design, technical implementation, planning and design, and deployment suggestions for cloud DCNs based on the service challenges DCNs encounter. It starts by describing the overall architecture and technical evolution of DCNs, with the aim of helping readers understand the development of DCNs. It then proceeds to explain the design and implementation of cloud DCNs, including the service model of a single data center (DC), construction of physical and logical networks of DCs, construction of multiple DCNs, and security solutions of DCs. Next, this book dives deep into practices of cloud DCN deployment based on real-world cases to help readers better understand how to build cloud DCNs. Finally, this book introduces DCN openness and some of the hottest forward-looking technologies. In summary, you can use this book as a reference to help you to build secure, reliable, efficient, and open cloud DCNs. It is intended for technical professionals of enterprises, research institutes, information departments, and DCs, as well as teachers and students of computer network-related majors in colleges and universities. Authors Lei Zhang Mr. Zhang is the Chief Architect of Huawei's DCN solution. He has more than 20 years' experience in network product and solution design, as well as a wealth of expertise in product design and development, network planning and design, and network engineering project implementation. He has led the design and deployment of more than 10 large-scale DCNs for Fortune Global 500 companies worldwide. Le Chen Mr. Chen is a Huawei DCN Solution Documentation Engineer with eight years' experience in developing documents related to DCN products and solutions. He has participated in the design and delivery of multiple large-scale enterprise DCNs. Mr. Chen has written many popular technical document series, such as DCN Handbook and BGP Topic.

This book focuses primarily on both technical and business aspects needed to select, design, develop and deploy control application (or product) successfully for multiple components in building systems. Designing and deploying a control application require multiple steps such as sensing, system dynamics modelling, algorithms, and testing. This may involve choosing an appropriate methodology and technique at multiple stages during the development process. Understanding the pros and cons of such techniques, most importantly being aware of practically possible approaches in the entire ecosystem, is critical in choosing the best framework and system application for different parts of building systems. Providing a wide overview of the state-of art in controls and building systems, providing guidance on developing an end-to-end system in relation to business fundamentals (distribution channels, stakeholders, marketing, supply-chain and financial management), the book is ideal for fourth-year control/mechanical/electrical engineering undergraduates, graduate students, and practitioners including business leaders concerned with smart building technology.

This book focuses primarily on both technical and business aspects needed to select, design, develop and deploy control application (or product) successfully for multiple components in building systems. Designing and deploying a control application require multiple steps such as sensing, system dynamics modelling, algorithms, and testing. This may involve choosing an appropriate methodology and technique at multiple stages during the development process. Understanding the pros and cons of such techniques, most importantly being aware of practically possible approaches in the entire ecosystem, is critical in choosing the best framework and system application for different parts of building systems. Providing a wide overview of the state-of art in controls and building systems, providing guidance on developing an end-to-end system in relation to business fundamentals (distribution channels, stakeholders, marketing, supply-chain and financial management), the book is ideal for fourth-year control/mechanical/electrical engineering undergraduates, graduate students, and practitioners including business leaders concerned with smart building technology.

This book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of Artificial Intelligence. The book provides a premier interdisciplinary platform to present practical challenges and adopted solutions. The book addresses the complete functional framework workflow in Artificial Intelligence technology. It explores the basic and high-level concepts and can serve as a manual for the industry for beginners and the more advanced. It covers intelligent and automated systems and its implications to the real-world, and offers data acquisition and case studies related to data-intensive technologies in AI-based applications. The book will be of interest to researchers, professionals, scientists, professors, students of computer science engineering, electronics and communications, as well as information technology.

Originally published in 1995, Large Deviations for Performance Analysis consists of two synergistic parts. The first half develops the theory of large deviations from the beginning, through recent results on the theory for processes with boundaries, keeping to a very narrow path: continuous-time, discrete-state processes. By developing only what is needed for the applications, the theory is kept to a manageable level, both in terms of length and in terms of difficulty. Within its scope, the treatment is detailed, comprehensive and self-contained. As the book shows, there are sufficiently many interesting applications of jump Markov processes to warrant a special treatment. The second half is a collection of applications developed at Bell Laboratories. The applications cover large areas of the theory of communication networks: circuit switched transmission, packet transmission, multiple access channels, and the M/M/1 queue. Aspects of parallel computation are covered as well including, basics of job allocation, rollback-based parallel simulation, assorted priority queueing models that might be used in performance models of various computer architectures, and asymptotic coupling of processors. These applications are thoroughly analysed using the tools developed in the first half of the book.