The ability of parallel computing to process large data sets and handle time-consuming operations has resulted in unprecedented advances in biological and scientific computing, modeling, and simulations. Exploring these recent developments, the Handbook of Parallel Computing: Models, Algorithms, and Applications provides comprehensive coverage on a

This unique treatment systematically interprets a spectrum of importance measures to provide a comprehensive overview of their applications in the areas of reliability, network, risk, mathematical programming, and optimization. Investigating the precise relationships among various importance measures, it describes how they are modelled and combined with other design tools to allow users to solve readily many real-world, large-scale decision-making problems. Presenting the state-of-the-art in network analysis, multistate systems, and application in modern systems, this book offers a clear and complete introduction to the topic. Through describing the reliability importance and the fundamentals, it covers advanced topics such as signature of coherent systems, multi-linear functions, and new interpretation of the mathematical programming problems. Key highlights: Generalizes the concepts behind importance measures (such as sensitivity and perturbation analysis, uncertainty analysis, mathematical programming, network designs), enabling readers to address large-scale problems within various fields effectively Covers a large range of importance measures, including those in binary coherent systems, binary monotone systems, multistate systems, continuum systems, repairable systems, as well as importance measures of pairs and groups of components Demonstrates numerical and practical applications of importance measures and the related methodologies, including risk analysis in nuclear power plants, cloud computing, software reliability and more Provides thorough comparisons, examples and case studies on relations of different importance measures, with conclusive results based on the authors’ own research Describes reliability design such as redundancy allocation, system upgrading and component assignment. This book will benefit researchers and practitioners interested in systems design, reliability, risk and optimization, statistics, maintenance, prognostics and operations. Readers can develop feasible approaches to solving various open-ended problems in their research and practical work. Software developers, IT analysts and reliability and safety engineers in nuclear, telecommunications, offshore and civil industries will also find the book useful.

This book constitutes the refereed proceedings of the 6th International Workshop on Systems, Architectures, Modeling, and Simulation, SAMOS 2006, held in Samos, Greece on July 2006. The 47 revised full papers presented together with 2 keynote talks were thoroughly reviewed and selected from 130 submissions. The papers are organized in topical sections on system design and modeling, wireless sensor networks, processor design, dependable computing, architectures and implementations, and embedded sensor systems.

As information systems used for research and educational purposes have become more complex, there has been an increase in the need for new computing architecture. High performance and cloud computing provide reliable and cost-effective information technology infrastructure that enhances research and educational processes. Handbook of Research on High Performance and Cloud Computing in Scientific Research and Education presents the applications of cloud computing in various settings, such as scientific research, education, e-learning, ubiquitous learning, and social computing. Providing various examples, practical solutions, and applications of high performance and cloud computing; this book is a useful reference for professionals and researchers discovering the applications of information and communication technologies in science and education, as well as scholars seeking insight on how modern technologies support scientific research.

This book focuses on the latest trends and research results in Cooperative Networking This book discusses the issues involved in cooperative networking, namely, bottleneck resource management, resource utilization, servers and content, security, and so on. In addition, the authors address instances of cooperation in nature which actively encourage the development of cooperation in telecommunication networks. Following an introduction to the fundamentals and issues surrounding cooperative networking, the book addresses models of cooperation, inspirations of successful cooperation from nature and society, cooperation in networking (for e.g. Peer-to-Peer, wireless ad-hoc and sensor, client-server, and autonomous vehicular networks), cooperation and ambient networking, cooperative caching, cooperative networking for streaming media content, optimal node-task allocation, heterogeneity issues in cooperative networking, cooperative search in networks, and security and privacy issues with cooperative networking. It contains contributions from high profile researchers and is edited by leading experts in this field. Key Features: Focuses on higher layer networking Addresses the latest trends and research results Covers fundamental concepts, models, advanced topics and performance issues in cooperative networking Contains contributions from leading experts in the field Provides an insight into the future direction of cooperative networking Includes an accompanying website containing PowerPoint slides and a glossary of terms (www.wiley.com/go/obaidat_cooperative) This book is an ideal reference for researchers and practitioners working in the field. It will also serve as an excellent textbook for graduate and senior undergraduate courses in computer science, computer engineering, electrical engineering, software engineering, and information engineering and science.

Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the