Smarter, faster prep for the SSCP exam The (ISC)(2) SSCP Official Practice Tests, 2nd Edition is the only (ISC)(2)-endorsed set of practice questions for the Systems Security Certified Practitioner (SSCP). This book's first seven chapters cover each of the seven domains on the SSCP exam with sixty or more questions per domain, so you can focus your study efforts exactly where you need more review. When you feel well prepared, use the two complete practice exams from Sybex's online interactive learning environment as time trials to assess your readiness to take the exam.: Coverage of all exam objectives, including: Security Operations and Administration Access Controls Risk Identification, Monitoring and Analysis Incident Response and Recovery Cryptography Network and Communications Security Systems and Application Security SSCP certification demonstrates you have the advanced technical skills and knowledge to implement, monitor and administer IT infrastructure using security best practices, policies and procedures. It's ideal for students pursuing cybersecurity degrees as well as those in the field looking to take their careers to the next level.

Systems Programming: Designing and Developing Distributed Applications explains how the development of distributed applications depends on a foundational understanding of the relationship among operating systems, networking, distributed systems, and programming. Uniquely organized around four viewpoints (process, communication, resource, and architecture), the fundamental and essential characteristics of distributed systems are explored in ways which cut across the various traditional subject area boundaries. The structures, configurations and behaviours of distributed systems are all examined, allowing readers to explore concepts from different perspectives, and to understand systems in depth, both from the component level and holistically.

This volume presents papers from the 10th Working Conference of the IFIP WG 8.6 on the adoption and diffusion of information systems and technologies. This book explores the dynamics of how some technological innovation efforts succeed while others fail. The book looks to expand the research agenda, paying special attention to the areas of theoretical perspectives, methodologies, and organizational sectors.

* Network traffic is a type of fractal time series, attracting the interests of not only computer scientists but the scientists from various fields, ranging from statistics to engineering * Innovatively presents a traffic bound named by the author * Further proves the existing identity in min-plus convolution system and the computation formula of the identity

Project or program health checks provide tremendous value to businesses and pay for themselves by multiples of magnitude. No matter how well a project or program is performing, there are always activities that can provide better value, reduce costs, or introduce more innovation. IT project and program health checks can help organizations reach their goals and dramatically improve Return on Investment (ROI). IT Project Health Checks: Driving Successful Implementation and Multiples of Business Value offers a proven approach for evaluating IT projects or programs in order to determine how they are performing and how the eventual outcome for the initiative is currently trending. The project or program health checks provide a set of techniques that produce actionable recommendations that can be applied for any combination of the following outcomes: Drive more business and technical value from a program Set a project or program back on track for successful implementation as defined by executive management Rescue a program that is heading towards failure Act as additional insurance for initiatives that are too important to fail Protect executive careers by creating transparency within the inner workings of complex initiatives. The book shows how a review can quickly identify whether an initiative needs to be rescued even when the project team is not aware that it is hurtling towards failure. It also provides techniques for driving business value even when a project team believes it's been stretched as much as possible. Other outcomes covered in this book include: Objectively develop a project Health-Check Scorecard that establishes how well a project is doing and the direction it is headed Demonstrate how to drive business value from an IT program regardless of how well or badly it is tracking Provide surgical advice to improve a project's outcome How to use the many templates and sample deliverables to get a quick start on your own health check. Designed to provide significant value to any member of a project team, program team, stakeholders, sponsors, business users, system integrators, trainers, and IT professionals, this book can help find opportunities to drive multiples of business value and exceed project success metrics.

This book presents essential perspectives on digital convolutions in wireless communications systems and illustrates their corresponding efficient real-time field-programmable gate array (FPGA) implementations. FPGAs or generic all programmable devices will soon become widespread, serving as the "brains" of all types of real-time smart signal processing systems, like smart networks, smart homes and smart cities. The book examines digital convolution by bringing together the following main elements: the fundamental theory behind the mathematical formulae together with corresponding physical phenomena; virtualized algorithm simulation together with benchmark real-time FPGA implementations; and detailed, state-of-the-art case studies on wireless applications, including popular linear convolution in digital front ends (DFEs); nonlinear convolution in digital pre-distortion (DPD) enabled high-efficiency wireless RF transceivers; and fast linear convolution in massive multiple-input multiple-output (MIMO) systems. After reading this book, students and professionals will be able to: * Understand digital convolution with inside-out information: discover what convolution is, why it is important and how it works. * Enhance their FPGA design skills, i.e., enhance their FPGA-related prototyping capability with model-based hands-on examples. * Rapidly expand their digital signal processing (DSP) blocks: to examine how to rapidly and efficiently create (DSP) functional blocks on a programmable FPGA chip as a reusable intellectual property (IP) core. * Upgrade their expertise as both "thinkers" and "doers": minimize/close the gap between mathematical equations and FPGA implementations for existing and emerging wireless applications.

Network infrastructures are growing rapidly to meet the needs of business, but the required repolicing and reconfiguration provide challenges that need to be addressed. The software-defined network (SDN) is the future generation of Internet technology that can help meet these challenges of network management. This book includes quantitative research, case studies, conceptual papers, model papers, review papers, and theoretical backing on SDN. This book investigates areas where SDN can help other emerging technologies deliver more efficient services, such as IoT, industrial IoT, NFV, big data, blockchain, cloud computing, and edge computing. The book demonstrates the many benefits of SDNs, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. The book demonstrates the many benefits of SDN, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. Chapters in the volume address: Design considerations for security issues and detection methods State-of-the-art approaches for mitigating DDos attacks using SDN Big data using Apache Hadoop for processing and analyzing large amounts of data Different tools used for attack simulation Network policies and policy management approaches that are widely used in the context of SDN Dynamic flow tables, or static flow table management A new four-tiered architecture that includes cloud, SDN-controller, and fog computing Architecture for keeping computing resources available near the industrial IoT network through edge computing The impact of SDN as an innovative approach for smart city development More. The book will be a valuable resource for SDN researchers as well as academicians, research scholars, and students in the related areas.

Translating traditional coaching methods and competencies for use in the online world, this informative and timely guide shows coaches how to transform their face-to-face practice into one that utilises technological means of communication with clients, mentors, and everyone else associated with their practice. The book offers up-to-the-minute practical and ethical information from two world-expert coaches, leaning on their combined 50 years of experience and study. It covers the practice of online coaching via email, chat, audio/telephone and video methods, as well as the ethics of online coaching (including an ethical framework), case material, supervision, mentoring and training, and a look into the future of the coaching profession in light of technological developments and the culture of cyberspace. Whether you are a coach-in-training or established Coaching Master, this book is an accessible and invaluable tool for taking and maintaining your coaching services online.

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Digital transformation (DT) has become a buzzword. Every industry segment across the globe is consciously jumping toward digital innovation and disruption to get ahead of their competitors. In other words, every aspect of running a business is being digitally empowered to reap all the benefits of the digital paradigm. All kinds of digitally enabled businesses across the globe are intrinsically capable of achieving bigger and better things for their constituents. Their consumers, clients, and customers will realize immense benefits with real digital transformation initiatives and implementations. The much-awaited business transformation can be easily and elegantly accomplished with a workable and winnable digital transformation strategy, plan, and execution. There are several enablers and accelerators for realizing the much-discussed digital transformation. There are a lot of digitization and digitalization technologies available to streamline and speed up the process of the required transformation. Industrial Internet of Things (IIoT) technologies in close association with decisive advancements in the artificial intelligence (AI) space can bring forth the desired transitions. The other prominent and dominant technologies toward forming digital organizations include cloud IT, edge/fog computing, real-time data analytics platforms, blockchain technology, digital twin paradigm, virtual and augmented reality (VR/AR) techniques, enterprise mobility, and 5G communication. These technological innovations are intrinsically competent and versatile enough to fulfill the varying requirements for establishing and sustaining digital enterprises. Enterprise Digital Transformation: Technology, Tools, and Use Cases features chapters on the evolving aspects of digital transformation and intelligence. It covers the unique competencies of digitally transformed enterprises, IIoT use cases, and applications. It explains promising technological solutions widely associated with digital innovation and disruption. The book focuses on setting up and sustaining smart factories that are fulfilling the Industry 4.0 vision that is realized through the IIoT and allied technologies.

Provides motivation for developing mathematical models for telecommunications network power and energy efficiency modelling. Discusses factors impacting overall network power consumption. Includes types of network equipment and their power consumption profiles. Reviews basics of network power modelling including network segmentation, top-down and bottom-up models. Explores application of metrics for equipment, networks, and services.

In the 5G era, edge computing and new ecosystems of mobile microservices enable new business models, strategies, and competitive advantage. Focusing on microservices, this book introduces the essential concepts, technologies, and trade-offs in the edge computing architectural stack, providing for widespread adoption and dissemination. The book elucidates the concepts, architectures, well-defined building blocks, and prototypes for mobile microservice platforms and pervasive application development, as well as the implementation and configuration of service middleware and AI-based microservices. A goal-oriented service composition model is then proposed by the author, allowing for an economic assessment of connected, smart mobile services. Based on this model, costs can be minimized through statistical workload aggregation effects or backhaul data transport reduction, and customer experience and safety can be enhanced through reduced response times. This title will be a useful guide for students and IT professionals to get started with microservices and when studying the use of microservices in pervasive applications. It will also appeal to researchers and students studying software architecture and service-oriented computing, and especially those interested in edge computing, pervasive computing, the Internet of Things, and mobile microservices.

This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects. The integration of high-frequency air interfaces into 5G+ wireless networks can relieve the congested radio frequency (RF) bands. Visible light communication (VLC) is now emerging as a promising candidate for future generations of HetNets. Heterogeneous RF-optical networks combine the high throughput of visible light and the high reliability of RF. However, when implementing these HetNets in mobile scenarios, several challenges arise from both planning and operational perspectives. Since the mmWave, terahertz, and visible light bands share similar wave propagation characteristics, the concepts presented here can be broadly applied in all such bands. To facilitate the planning of RF-optical HetNets, the authors present an algorithm that specifies the joint optimal densities of the base stations by drawing on stochastic geometry in order to satisfy the users' quality-of-service (QoS) demands with minimum network power consumption. From an operational perspective, the book explores vertical handovers and multi-homing using a cooperative framework. For vertical handovers, it employs a data-driven approach based on deep neural networks to predict abrupt optical outages; and, on the basis of this prediction, proposes a reinforcement learning strategy that ensures minimal network latency during handovers. In terms of multi-homing support, the authors examine the aggregation of the resources from both optical and RF networks, adopting a two-timescale multi-agent reinforcement learning strategy for optimal power allocation. Presenting comprehensive planning and operational strategies, the book allows readers to gain an in-depth grasp of how to integrate future coexisting networks at high-frequency bands in a cooperative manner, yielding reliable and high-speed 5G+ HetNets.

This book presents a comprehensive overview of enterprise architecture management with a specific focus on the business aspects. While recent approaches to enterprise architecture management have dealt mainly with aspects of information technology, this book covers all areas of business architecture from business motivation and models to business execution. The book provides examples of how architectural thinking can be applied in these areas, thus combining different perspectives into a consistent whole. In-depth experiences from end-user organizations help readers to understand the abstract concepts of business architecture management and to form blueprints for their own professional approach. Business architecture professionals, researchers, and others working in the field of strategic business management will benefit from this comprehensive volume and its hands-on examples of successful business architecture management practices.

"Collaboration with Cloud Computing "discusses the risks associated with implementing these technologies across the enterprise and provides you with expert guidance on how to manage risk through policy changes and technical solutions.

Drawing upon years of practical experience and using numerous examples and case studies, author Ric Messier discusses: The evolving nature of information securityThe risks, rewards, and security considerations when implementing SaaS, cloud computing and VoIP Social media and security risks in the enterprise The risks and rewards of allowing remote connectivity and accessibility to the enterprise network
Discusses the risks associated with technologies such as social media, voice over IP (VoIP) and cloud computing and provides guidance on how to manage that risk through policy changes and technical solutionsPresents a detailed look at the risks and rewards associated with cloud computing and storage as well as software as a service (SaaS) and includes pertinent case studiesExplores the risks associated with the use of social media to the enterprise networkCovers the bring-your-own-device(BYOD) trend, including policy considerations and technical requirements"

Mobile devices are ubiquitous; therefore, mobile device forensics is absolutely critical. Whether for civil or criminal investigations, being able to extract evidence from a mobile device is essential. This book covers the technical details of mobile devices and transmissions, as well as forensic methods for extracting evidence. There are books on specific issues like Android forensics or iOS forensics, but there is not currently a book that covers all the topics covered in this book. Furthermore, it is such a critical skill that mobile device forensics is the most common topic the Author is asked to teach to law enforcement. This is a niche that is not being adequately filled with current titles. An In-Depth Guide to Mobile Device Forensics is aimed towards undergraduates and graduate students studying cybersecurity or digital forensics. It covers both technical and legal issues, and includes exercises, tests/quizzes, case studies, and slides to aid comprehension.

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

The volume addresses a selection of diverse topics in such areas as: machine learning based intelligent systems for healthcare applications of artificial intelligence the Internet of Things, intelligent data analytics techniques, intelligent network systems and applications, and inequalities and process control systems.

The fourth edition is again an "all-in-one" combination of basic theory and practical exercises with software and data available from the Springer server. Potential readers / users are students of Photogrammetry, Geodesy, Geography and other sciences, but also all who are interested in this topic. No prior knowledge is necessary, except the handling of standard PCs. Theory is presented true to the motto "as little as possible, but as much as necessary". The main part of the book contains several tutorials. In increasing complexity, accompanied by texts explaining further theory, the reader can proceed step by step through the particular working parts. All intermediate as well as the final results are discussed with reference to accuracy and error handling, and included in the data sets to provide controls. Most of the standard work in Digital Photogrammetry is shown and trained, for example scanning, image orientation, stereo plotting, aerial triangulation measurement (manual and automatic), block adjustment, automatic creation of surface models via image matching, creation of ortho images and mosaics, and others. Examples of both aerial and close-range photogrammetry present the power of this kind of measurement techniques. 3-D images can be viewed with the accompanying 3-D glasses. During the time since the last edition, the software development went on, and therefore it was necessary to adopt the text to the actual program versions which were also tested to work properly under MS Windows 10. Few options which are obsolete nowadays were removed, some new options were added, the handling of the software was simplified in several places, and so on. For the use of own images taken with a custom digital camera, a new chapter offers an easy way of lens calibration and explains how to get good results with a minimum of work. The software is not limited to the example data included but may be used for personal projects. Part of the book comprises a complete description of the software.

The insertion of communication networks in feedback control loops complicates analysis and synthesis of cyber-physical systems (CPSs), and network-induced uncertainties may degrade system control performance. Thus, this book researches networked delay compensation and event-triggered control approaches for a series of CPSs subject to network-induced uncertainties. The authors begin with an introduction to the concepts and challenges of CPSs, followed by an overview of networked control approaches and event-triggered control strategies in CPSs. Then, networked delay compensation and event-triggered control approaches are proposed for CPSs with network communication delay, data dropout, signal quantization, and event-triggered communication. More specifically, networked delay compensation approaches are proposed for linear/nonlinear networked controlled plants with time-varying and random network communication delays and data dropouts. To reduce computational burden and network communication loads in CPSs, event-triggered control, self-triggered control, co-design of event-triggered control and quantized control techniques, and event-triggered disturbance rejection control approaches are also presented. This book is an essential text for researchers and engineers interested in cybersecurity, networked control, and CPSs. It would also prove useful for graduate students in the fields of science, engineering, and computer science.

Industry 4.0 is a challenge for today's businesses. It's a concept that encompasses the technological innovations of automation, control, and information technology, as it's applied to manufacturing processes. It's a new topic that recently emerged in academia and industry, with few books that target both management and engineering. This book will cover the new advances and the way to manage competitive organizations. The chapters will include terms of theory, evidence, and/or methodology, and significantly advance social scientific research. This book: Focuses on the latest and most recent research findings occurring on the topic of Industry 4.0 Presents the ways companies around the world are facing today's technological challenges Assists researchers and practitioners in selecting the correct options and strategies to manage competitive organizations Provides recent advances in international studies Encompasses the main technological innovations in the fields of automation, control, and information technology applied to the manufacturing processes Industry 4.0: Challenges, Trends, and Solutions in Manangment and Engineering is designed to increase the knowledge and effectiveness of all managers and engineers in all organizations and activity sectors Carolina Machado has been teaching in the Human Resources Management subjects since 1989 at University of Minho, Portugal. She has been an associate professor since 2004, with experience and research interest areas in the field of Human Resource Management, International Human Resource Management, Human Resource Management in SMEs, Training and Development, Emotional Intelligence, Management Change, Knowledge Management, and Management/HRM in the Digital Age. She is head of the Department of Management and head of the Human Resources Management Work Group at University of Minho, as well as chief editor of the International Journal of Applied Management Sciences and Engineering (IJAMSE). J. Paulo Davim is a professor at the Department of Mechanical Engineering of the University of Aveiro, Portugal. He has more than 30 years of teaching and research experience in Manufacturing, Materials, Mechanical, and Industrial Engineering, with special emphasis in Machining & Tribology. He has also interest in Management, Engineering Education, and Higher Education for Sustainability. He has worked as evaluator of projects for ERC (European Research Council) and other international research agencies.

Data is an intrinsic part of our daily lives. Everything we do is a data point. Many of these data points are recorded with the intent to help us lead more efficient lives. We have apps that track our workouts, sleep, food intake, and personal finance. We use the data to make changes to our lives based on goals we have set for ourselves. Businesses use vast collections of data to determine strategy and marketing. Data scientists take data, analyze it, and create models to help solve problems. You may have heard of companies having data management teams or chief information officers (CIOs) or chief data officers (CDOs), etc. They are all people who work with data, but their function is more related to vetting data and preparing it for use by data scientists. The jump from personal data usage for self-betterment to mass data analysis for business process improvement often feels bigger to us than it is. In turn, we often think big data analysis requires tools held only by advanced degree holders. Although advanced degrees are certainly valuable, this book illustrates how it is not a requirement to adequately run a data science project. Because we are all already data users, with some simple strategies and exposure to basic analytical software programs, anyone who has the proper tools and determination can solve data science problems. The process presented in this book will help empower individuals to work on and solve data-related challenges. The goal of this book is to provide a step-by-step guide to the data science process so that you can feel confident in leading your own data science project. To aid with clarity and understanding, the author presents a fictional restaurant chain to use as a case study, illustrating how the various topics discussed can be applied. Essentially, this book helps traditional businesspeople solve data-related problems on their own without any hesitation or fear. The powerful methods are presented in the form of conversations, examples, and case studies. The conversational style is engaging and provides clarity.

A database management system (DBMS) is a collection of programs that enable users to create and maintain a database; it also consists of a collection of interrelated data and a set of programs to access that data. Hence, a DBMS is a general-purpose software system that facilitates the processes of defining, constructing, and manipulating databases for various applications. The primary goal of a DBMS is to provide an environment that is both convenient and efficient to use in retrieving and storing database information. It is an interface between the user of application programs, on the one hand, and the database, on the other. The objective of Database Management System: An Evolutionary Approach, is to enable the learner to grasp a basic understanding of a DBMS, its need, and its terminologies discern the difference between the traditional file-based systems and a DBMS code while learning to grasp theory in a practical way study provided examples and case studies for better comprehension This book is intended to give under- and postgraduate students a fundamental background in DBMSs. The book follows an evolutionary learning approach that emphasizes the basic concepts and builds a strong foundation to learn more advanced topics including normalizations, normal forms, PL/SQL, transactions, concurrency control, etc. This book also gives detailed knowledge with a focus on entity-relationship (ER) diagrams and their reductions into tables, with sufficient SQL codes for a more practical understanding.

In this book, Edosa explores common challenges which limit the value that organisations can get from data. What makes his book unique is that he also tackles one of the unspoken barriers to data adoption-fear. Fear of the unknown, fear of the intangible, fear of the investment needed and, yes, fear of losing your job to a machine. With his talent for distilling clarity from complexity, Edosa tackles this and many other challenges. -Tim Carmichael, Chief Data Officer, Chalhoub Group This book offers fresh insight about how to solve the interactional frictions that hamper the flow of data, information and knowledge across organisations. Yet, rather than being stuck with endless polarising debates such as breaking down silos, it shifts focus back towards the ultimate "to what end." -Jacky Wright, Chief Digital Officer (CDO), Microsoft US If you care about AI transformation, empowering people or advancing organisational success in an increasingly digital world, then you should read this book. -Yomi Ibosiola, Chief Data and Analytics Officer, Union Bank A retail giant already struggling due to the Covid-19 pandemic was faced with a disastrous situation when-at the end of a critical investment in an artificial intelligence project that had been meant to save money-it suddenly discovered that its implementation was likely to leave it worse off. An entire critical service stream within an insurer's production system crashed. This critical failure resulted in the detentions of fully insured motorists for allegedly not carrying required insurance. Making Data Work details these two scenarios as well as others illustrating the consequences that arise when organizations do not know how to make data work properly. It is a journey to determine what to do to "make data work" for ourselves and for our organisations. It is a journey to discover how to bring it all together so organisations can enable digital transformation, empower people, and advance organisational success. It is the journey to a world where data and technology finally live up to the hype and deliver better human outcomes, where artificial intelligence can move us from reacting to situations to predicting future occurrences and enabling desirable possibilities.

From Markov Jump Processes to Spatial Queues aims to develop a unified theory of spatial queues that yields concrete results for the performance analysis of mobile communication networks. A particular objective is to develop the most natural generalization of existing concepts (e.g. the BMAP) toward the needs of mobile communication networks. To these belong the spatial distribution of batch arrivals and users in the system as well as time-inhomogeneous (e.g. periodic) arrival intensities and user movements.

One of the major recent challenges for the stochastic modelling of communication systems is the emergence of wireless networks, which are used by more and more subscribers today. The main new feature of those, which is not covered by classical queuing theory, clearly is the importance of the user location within the area that is served by the base stations of the network.

In the framework of queuing theory, this opens up the natural extension of classical queuing models towards queues with a structured space in which users are served. The present book is intended to introduce this extension under the name of spatial queues. The main point of view and the general approach will be that of Markov jump processes. We start with a closer look into the theory. Then we present new results for the theory of stochastic processes as well as for classical queuing theory. Finally we introduce the new concepts of spatial Markovian arrival processes and spatial queues.

The main text is divided into three parts. The first part provides a new presentation of the theory of Markov jump processes. We derive a number of new results, especially for time-inhomogeneous processes, which have been neglected too much in the current textbooks on stochastic processes. For the first time, the class of Markov-additive jump processes is analysed in detail. This extends and unifies all Markovian arrival processes that have been proposed up to now (including arrivals for fluid queues) and provides a foundation for the subsequent introduction of spatial Markovian arrival processes.

The second part contains new results for classical queues with BMAP input. These include the first explicit formulae for the distribution of periodic queues. The class of fluid Markovian arrival processes is introduced, and we give statistical estimates for the parameters of a BMAP.

In the third part, the concepts of spatial Markovian arrival processes (abbreviated: SMAPs) and spatial queues are introduced. After that, periodic spatial Markovian queues are analysed as a model for the cells of a wireless communication network.
From Markov Jump Processes to Spatial Queues is intended to reach queuing theorists, researchers in the field of communication systems, as well as engineers with some background in probability theory. Furthermore, it is suitable as a textbook for advanced queuing theory on the graduate or post-graduate level.