This volume presents meta-heuristics approaches for Grid scheduling problems. It brings new ideas, analysis, implementations and evaluation of meta-heuristic techniques for Grid scheduling, which make this volume novel in several aspects.

During the past decades scheduling has been among the most studied op- mization problemsanditisstillanactiveareaofresearch!Schedulingappears in many areas of science, engineering and industry and takes di?erent forms depending on the restrictions and optimization criteria of the operating en- ronments [8]. For instance, in optimization and computer science, scheduling has been de?ned as “the allocation of tasks to resources over time in order to achieve optimality in one or more objective criteria in an e?cient way” and in production as “production schedule, i. e. , the planning of the production or the sequence of operations according to which jobs pass through machines and is optimal with respect to certain optimization criteria. ” Although there is a standardized form of stating any scheduling problem, namely “e?cient allocation ofn jobs onm machines –which can process no more than one activity at a time– with the objective to optimize some - jective function of the job completion times”, scheduling is in fact a family of problems. Indeed, several parameters intervene in the problem de?nition: (a) job characteristics (preemptive or not, precedence constraints, release dates, etc. ); (b) resource environment (single vs. parallel machines, un- lated machines, identical or uniform machines, etc. ); (c) optimization criteria (minimize total tardiness, the number of late jobs, makespan, ?owtime, etc. ; maximize resource utilization, etc. ); and, (d) scheduling environment (static vs. dynamic,intheformerthenumberofjobstobeconsideredandtheirready times are available while in the later the number of jobs and their charact- istics change over time).

The book covers cutting-edge and advanced research in modelling and graphics. Gathering high-quality papers presented at the First International Conference on Emerging Technology in Modelling and Graphics, held from 6 to 8 September 2018 in Kolkata, India, it addresses topics including: image processing and analysis, image segmentation, digital geometry for computer imaging, image and security, biometrics, video processing, medical imaging, and virtual and augmented reality.

This book comprises select proceedings of the International Conference on Advances in Electrical and Computer Technologies 2020 (ICAECT 2020). The papers presented in this book are peer-reviewed and cover latest research in electrical, electronics, communication and computer engineering. Topics covered include smart grids, soft computing techniques in power systems, smart energy management systems, power electronics, feedback control systems, biomedical engineering, geo informative systems, grid computing, data mining, image and signal processing, video processing, computer vision, pattern recognition, cloud computing, pervasive computing, intelligent systems, artificial intelligence, neural network and fuzzy logic, broad band communication, mobile and optical communication, network security, VLSI, embedded systems, optical networks and wireless communication. The volume can be useful for students and researchers working in the different overlapping areas of electrical, electronics and communication engineering.

This book constitutes the refereed post-conference proceedings of the 5th Russian Supercomputing Days, RuSCDays 2019, held in Moscow, Russia, in September 2019. The 60 revised full papers presented were carefully reviewed and selected from 127 submissions. The papers are organized in the following topical sections: parallel algorithms; supercomputer simulation; HPC, BigData, AI: architectures, technologies, tools; and distributed and cloud computing.

This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.

This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.

The book is compilation of technical papers presented at International Research Symposium on Computing and Network Sustainability (IRSCNS 2016) held in Goa, India on 1st and 2nd July 2016. The areas covered in the book are sustainable computing and security, sustainable systems and technologies, sustainable methodologies and applications, sustainable networks applications and solutions, user-centered services and systems and mobile data management. The novel and recent technologies presented in the book are going to be helpful for researchers and industries in their advanced works.

One of the most challenging issues in modelling today's large-scale computational systems is to effectively manage highly parametrised distributed environments such as computational grids, clouds, ad hoc networks and P2P networks. Next-generation computational grids must provide a wide range of services and high performance computing infrastructures. Various types of information and data processed in the large-scale dynamic grid environment may be incomplete, imprecise, and fragmented, which complicates the specification of proper evaluation criteria and which affects both the availability of resources and the final collective decisions of users. The complexity of grid architectures and grid management may also contribute towards higher energy consumption. All of these issues necessitate the development of intelligent resource management techniques, which are capable of capturing all of this complexity and optimising meaningful metrics for a wide range of grid applications. This book covers hot topics in the design, administration and management of dynamic grid environments with a special emphasis on the preferences and autonomous decisions of system users, secure access to the processed data and services, and application of green technologies. It features advanced research related to scalable genetic-based heuristic approaches to grid scheduling, whereby new scheduling criteria, such as system reliability, security, and energy consumption are incorporated into a general scheduling model. This book may be a valuable reference for students, researchers, and practitioners who work on – or who are interested in joining -- interdisciplinary research efforts in the areas of distributed and evolutionary computation.

This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2014, CISIS 2014 and ICEUTE 2014, all conferences held in the beautiful and historic city of Bilbao (Spain), in June 2014. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 9th SOCO 2014 International Program Committee selected 31 papers which are published in these conference proceedings. In this relevant edition a special emphasis was put on the organization of special sessions. One special session was organized related to relevant topics as: Soft Computing Methods in Manufacturing and Management Systems. The aim of the 7th CISIS 2014 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of Computational Intelligence, Information Security, and Data Mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a through peer-review process, the CISIS 2014 International Program Committee selected 23 papers and the 5th ICEUTE 2014 International Program Committee selected 2 papers which are published in these conference proceedings as well.