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This book constitutes the refereed joint proceedings of eight internationl workshops held in conjunction with the Third International Symposium on Parallel and Distributed Processing and Applications, ISPA 2005, held in Nanjing, China in November 2005 (see LNCS 3758). The 71 revised full papers presented were carefully reviewed and selected from 323 submissions. The papers of the eight workshops are very specific and contribute to enlarging the spectrum of the more general topics treated in the ISPA 2005 main conference. Topics addressed are applications and economics of peer-to-peer systems (AEPP 2005), advanced storage technology and autonomic distributed data (ASTD 2005), bioinformatics (BIOS 2005), grid computing in china (GCIC 2005), information assurance in distributed systems (IADS 2005), mobile ad-hoc and ubiquitous sensor networks (MASN 2005), service grid computing and applications (SGCA 2005), and Web information systems and applications (WISA 2005).
This book constitutes the refereed proceedings of the Third International Symposium on Parallel and Distributed Processing and Applications, ISPA 2005, held in Nanjing, China in November 2005. The 90 revised full papers and 19 revised short papers presented together with 3 keynote speeches and 2 tutorials were carefully reviewed and selected from 645 submissions. The papers are organized in topical sections on cluster systems and applications, performance evaluation and measurements, distributed algorithms and systems, fault tolerance and reliability, high-performance computing and architecture, parallel algorithms and systems, network routing and communication algorithms, security algorithms and systems, grid applications and systems, database applications and data mining, distributed processing and architecture, sensor networks and protocols, peer-to-peer algorithms and systems, internet computing and Web technologies, network protocols and switching, and ad hoc and wireless networks.
This book provides basic and fundamental knowledge of various aspects of energy-aware computing at the component, software, and system level. It provides a broad range of topics dealing with power-, energy-, and temperature-related research areas for individuals from industry and academia.
Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. As computers increase in speed and power, their energy issues become more and more prevalent. The need to develop and promote environmentally friendly computer technologies and systems has also come to the forefront
This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.
Design of complex artifacts and systems requires the cooperation of multidisciplinary design teams using multiple sophisticated commercial and non-commercial engine- ing tools such as CAD tools, modeling, simulation and optimization software, en- neering databases, and knowledge-based systems. Individuals or individual groups of multidisciplinary design teams usually work in parallel and independently with various engineering tools, which are located on different sites, often for quite a long period of time. At any moment, individual members may be working on different versions of a design or viewing the design from various perspectives, at different levels of details. In order to meet these requirements, it is necessary to have efficient comput- supported collaborative design systems. These systems should not only automate in- vidual tasks, in the manner of traditional computer-aided engineering tools, but also enable individual members to share information, collaborate, and coordinate their activities within the context of a design project. Based on close international collaboration between the University of Technology of Compiègne in France and the Institute of Computing Technology of the Chinese Ac- emy of Sciences in the early 1990s, a series of international workshops on CSCW in Design started in 1996. In order to facilitate the organization of these workshops, an International Working Group on CSCW in Design (CSCWD) was established and an International Steering Committee was formed in 1998. The series was converted to int- national conferences in 2000 building on the success of the four previous workshops.
In the past decades, organizations had to face numerous challenges due to intensifying globalization, shorter innovation cycles and growing IT support. Business process management is seen as a comprehensive approach to address these challenges. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since organizations tend to have a huge number of such models, analysis techniques are required that ensure the quality of these process models in an automatic fashion. The goal of this doctoral thesis is the development of model refactoring techniques by integrating and applying concepts from the three main branches of theoretical linguistics: syntax, semantics, and pragmatics. The syntactical refactoring technique addresses linguistic issues that arise by expressing process behavior with natural language. The semantic refactoring technique reworks terminology with overlapping and synonymous meaning. The pragmatic refactoring technique provides recommendations for incompletely specified process models. All of the presented techniques have been evaluated with real-world process model repositories from various industries to demonstrate their applicability and efficiency.
Crowd computing, crowdsourcing, crowd-associated network (CrAN), crowd-assisted sensing are some examples of crowd-based concepts that harness the power of people on the web or connected via web-like infrastructure to do tasks that are often difficult for individual users or computers to do alone. This creates many challenging issues like assessing reliability and correctness of crowd generated information, delivery of data and information via crowd, middleware for supporting crowdsourcing and crowd computing tasks, crowd associated networking and its security, Quality of Information (QoI) issues, etc. This book compiles the latest advances in the relevant fields.
Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.