Big Data has been much in the news in recent years, and the advantages conferred by the collection and analysis of large datasets in fields such as marketing, medicine and finance have led to claims that almost any real world problem could be solved if sufficient data were available. This is of course a very simplistic view, and the usefulness of collecting, processing and storing large datasets must always be seen in terms of the communication, processing and storage capabilities of the computing platforms available. This book presents papers from the International Research Workshop, Advanced High Performance Computing Systems, held in Cetraro, Italy, in July 2014. The papers selected for publication here discuss fundamental aspects of the definition of Big Data, as well as considerations from practice where complex datasets are collected, processed and stored. The concepts, problems, methodologies and solutions presented are of much more general applicability than may be suggested by the particular application areas considered. As a result the book will be of interest to all those whose work involves the processing of very large data sets, exascale computing and the emerging fields of data science

The Helmholtz Association funded the ""Large-Scale Data Management and Analysis"" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities.

To help researchers from different areas of science understand and unlock the potential of the Polish Grid Infrastructure and to define their requirements and expectations, the following 13 pilot communities have been organized and involved in the PLGrid Plus project: Acoustics, AstroGrid-PL, Bioinformatics, Ecology, Energy Sector, Health Sciences, HEPGrid, Life Science, Materials, Metallurgy, Nanotechnologies, Quantum Chemistry and Molecular Physics, and SynchroGrid. The book describes the experience and scientific results achieved by the project partners. Chapters 1 to 8 provide a general overview of research and development activities in the framework of the project with emphasis on services for different scientific areas and an update on the status of the PL-Grid infrastructure, describing new developments in security and middleware. Chapters 9 to 13 discuss new environments and services which may be applied by all scientific communities. Chapters 14 to 36 present how the PLGrid Plus environments, tools and services are used in advanced domain specific computer simulations; these chapters present computational models, new algorithms, and ways in which they are implemented. The book also provides a glossary of terms and concepts. This book may serve as a resource for researchers, developers and system administrators working on efficient exploitation of available e-infrastructures, promoting collaboration and exchange of ideas in the process of constructing a common European e-infrastructure.

Scientific workflows have emerged as a key technology that assists scientists with the design, management, execution, sharing and reuse of in silico experiments. Workflow management systems simplify the management of scientific workflows by providing graphical interfaces for their development, monitoring and analysis. Nowadays, e-Science combines such workflow management systems with large-scale data and computing resources into complex research infrastructures. For instance, e-Science allows the conveyance of best practice research in collaborations by providing workflow repositories, which facilitate the sharing and reuse of scientific workflows. However, scientists are still faced with different limitations while reusing workflows. One of the most common challenges they meet is the need to select appropriate applications and their individual execution parameters. If scientists do not want to rely on default or experience-based parameters, the best-effort option is to test different workflow set-ups using either trial and error approaches or parameter sweeps. Both methods may be inefficient or time consuming respectively, especially when tuning a large number of parameters. Therefore, scientists require an effective and efficient mechanism that automatically tests different workflow set-ups in an intelligent way and will help them to improve their scientific results. This thesis addresses the limitation described above by defining and implementing an approach for the optimization of scientific workflows. In the course of this work, scientists’ needs are investigated and requirements are formulated resulting in an appropriate optimization concept. In a following step, this concept is prototypically implemented by extending a workflow management system with an optimization framework, including general mechanisms required to conduct workflow optimization. As optimization is an ongoing research topic, different algorithms are provided by pluggable extensions (plugins) that can be loosely coupled with the framework, resulting in a generic and quickly extendable system. In this thesis, an exemplary plugin is introduced which applies a Genetic Algorithm for parameter optimization. In order to accelerate and therefore make workflow optimization feasible at all, e-Science infrastructures are utilized for the parallel execution of scientific workflows. This is empowered by additional extensions enabling the execution of applications and workflows on distributed computing resources. The actual implementation and therewith the general approach of workflow optimization is experimentally verified by four use cases in the life science domain. All workflows were significantly improved, which demonstrates the advantage of the proposed workflow optimization. Finally, a new collaboration-based approach is introduced that harnesses optimization provenance to make optimization faster and more robust in the future.

This book constitutes the refereed proceedings of the Second International Conference on Security in Computer Networks and Distributed Systems, SNDS 2014, held in Trivandrum, India, in March 2014. The 32 revised full papers presented together with 9 short papers and 8 workshop papers were carefully reviewed and selected from 129 submissions. The papers are organized in topical sections on security and privacy in networked systems; multimedia security; cryptosystems, algorithms, primitives; system and network security; short papers. The workshop papers were presented at the following workshops: Second International Workshop on Security in Self-Organising Networks (Self Net 2014); Workshop on Multidisciplinary Perspectives in Cryptology and Information Security (CIS 2014); Second International Workshop on Trust and Privacy in Cyberspace (Cyber Trust 2014).