Large Scale Network Centric Distributed Systems

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issues (such as buffer organization, router delay, and flow control) to the high-level issues immediately concerning application or system users (including parallel programming, middleware, and OS support for such computing systems). Arranged in five parts, it explains and analyzes complex topics to an unprecedented degree: Part 1: Multicore and Many-Core (Mc) Systems-on-Chip Part 2: Pervasive/Ubiquitous Computing and Peer-to-Peer Systems Part 3: Wireless/Mobile Networks Part 4: Grid and Cloud Computing Part 5: Other Topics Related to Network-Centric Computing and Its Applications Large Scale Network-Centric Distributed Systems is an incredibly useful resource for practitioners, postgraduate students, postdocs, and researchers.

Addresses innovations in technology relating to the energy efficiency of a wide variety of contemporary computer systems and networks With concerns about global energy consumption at an all-time high, improving computer networks energy efficiency is becoming an increasingly important topic. Large-Scale Distributed Systems and Energy Efficiency: A Holistic View addresses innovations in technology relating to the energy efficiency of a wide variety of contemporary computer systems and networks. After an introductory overview of the energy demands of current Information and Communications Technology (ICT), individual chapters offer in-depth analyses of such topics as cloud computing, green networking (both wired and wireless), mobile computing, power modeling, the rise of green data centers and high-performance computing, resource allocation, and energy efficiency in peer-to-peer (P2P) computing networks. Discusses measurement and modeling of the energy consumption method Includes methods for energy consumption reduction in diverse computing environments Features a variety of case studies and examples of energy reduction and assessment Timely and important, Large-Scale Distributed Systems and Energy Efficiency is an invaluable resource for ways of increasing the energy efficiency of computing systems and networks while simultaneously reducing the carbon footprint.

Service-Oriented Infrastructures including Grid and Cloud Computing are technologies in a critical transition to wider adoption by business. Their use may enable enterprises to achieve optimal IT utilization, including sharing resources and services across enterprises and on-demand utilization of those made available by business partners over the network. This book is an essential reference for researchers and practitioners in service-oriented IT. It analyses a selection of common capabilities (services capturing reusable functionality of IT solutions) that have been applied to tackle challenging business problems and were validated by the BEinGRID consortium in real-life business trials covering most European market sectors.

This two-volume set LNCS 5870/5871 constitutes the refereed proceedings of the four confederated international conferences on Cooperative Information Systems (CoopIS 2009), Distributed Objects and Applications (DOA 2009), Information Security (IS 2009), and Ontologies, Databases and Applications of Semantics (ODBASE 2009), held as OTM 2009 in Vilamoura, Portugal, in November 2009. The 83 revised full papers presented together with 4 keynote talks were carefully reviewed and selected from a total of 234 submissions. Corresponding to the four OTM 2009 main conferences CoopIS, DOA, IS, and ODBASE the papers are organized in topical sections on workflow; process models; ontology challenges; network complexity; modeling cooperation; information complexity; infrastructure; information; aspect-oriented approaches for distributed middleware; distributed algorithms and communication protocols; distributed infrastructures for cluster and Grid computing; object-based, component-based, resource-oriented, event-oriented, and service-oriented middleware; peer-to-peer and centralized infrastructures; performance analysis of distributed computing systems; reliability, fault tolerance, quality of service, and real time support; self* properties in distributed middleware; software engineering for distributed middleware systems; security and privacy in a connected world; ubiquitous and pervasive computing; information systems security; privacy and authentication; security policies and verification; managing ontologies; using ontologies; event processing; dealing with heterogeneity; building knowledge bases; and XML and XML schema.

Cloud Computing: Theory and Practice provides students and IT professionals with an in-depth analysis of the cloud from the ground up. Beginning with a discussion of parallel computing and architectures and distributed systems, the book turns to contemporary cloud infrastructures, how they are being deployed at leading companies such as Amazon, Google and Apple, and how they can be applied in fields such as healthcare, banking and science. The volume also examines how to successfully deploy a cloud application across the enterprise using virtualization, resource management and the right amount of networking support, including content delivery networks and storage area networks. Developers will find a complete introduction to application development provided on a variety of platforms. Learn about recent trends in cloud computing in critical areas such as: resource management, security, energy consumption, ethics, and complex systems Get a detailed hands-on set of practical recipes that help simplify the deployment of a cloud based system for practical use of computing clouds along with an in-depth discussion of several projects Understand the evolution of cloud computing and why the cloud computing paradigm has a better chance to succeed than previous efforts in large-scale distributed computing

Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques. Data analytics are becoming an essential component for every organization and technologies such as health care, financial trading, Internet of Things, Smart Cities or Cyber Physical Systems. However, these diverse application domains give rise to new research challenges. In this context, the book provides a broad picture on the concepts, techniques, applications, and open research directions in this area. In addition, it serves as a single source of reference for acquiring the knowledge on emerging Big Data Analytics technologies.

Programming multi-core and many-core computing systems Sabri Pllana, Linnaeus University, Sweden Fatos Xhafa, Technical University of Catalonia, Spain Provides state-of-the-art methods for programming multi-core and many-core systems The book comprises a selection of twenty two chapters covering: fundamental techniques and algorithms; programming approaches; methodologies and frameworks; scheduling and management; testing and evaluation methodologies; and case studies for programming multi-core and many-core systems. Program development for multi-core processors, especially for heterogeneous multi-core processors, is significantly more complex than for single-core processors. However, programmers have been traditionally trained for the development of sequential programs, and only a small percentage of them have experience with parallel programming. In the past, only a relatively small group of programmers interested in High Performance Computing (HPC) was concerned with the parallel programming issues, but the situation has changed dramatically with the appearance of multi-core processors on commonly used computing systems. It is expected that with the pervasiveness of multi-core processors, parallel programming will become mainstream. The pervasiveness of multi-core processors affects a large spectrum of systems, from embedded and general-purpose, to high-end computing systems. This book assists programmers in mastering the efficient programming of multi-core systems, which is of paramount importance for the software-intensive industry towards a more effective product-development cycle. Key features: Lessons, challenges, and roadmaps ahead. Contains real world examples and case studies. Helps programmers in mastering the efficient programming of multi-core and many-core systems. The book serves as a reference for a larger audience of practitioners, young researchers and graduate level students. A basic level of programming knowledge is required to use this book.