Evolutionary Hierarchical Multi Criteria Metaheuristics For Scheduling In Large Scale Grid Systems

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.

Today’s highly parameterized large-scale distributed computing systems may be composed of a large number of various components (computers, databases, etc) and must provide a wide range of services. The users of such systems, located at different (geographical or managerial) network cluster may have a limited access to the system’s services and resources, and different, often conflicting, expectations and requirements. Moreover, the information and data processed in such dynamic environments may be incomplete, imprecise, fragmentary, and overloading. All of the above mentioned issues require some intelligent scalable methodologies for the management of the whole complex structure, which unfortunately may increase the energy consumption of such systems. An optimal energy utilization has reached to a point that many information technology (IT) managers and corporate executives are all up in arms to identify scalable solution that can reduce electricity consumption (so that the total cost of operation is minimized) of their respective large-scale computing systems and simultaneously improve upon or maintain the current throughput of the system. This book in its eight chapters, addresses the fundamental issues related to the energy usage and the optimal low-cost system design in high performance ``green computing’’ systems. The recent evolutionary and general metaheuristic-based solutions for energy optimization in data processing, scheduling, resource allocation, and communication in modern computational grids, could and network computing are presented along with several important conventional technologies to cover the hot topics from the fundamental theory of the ‘’green computing’’ concept and to describe the basic architectures of systems. This book points out the potential application areas and provides detailed examples of application case studies in low-energy computational systems. The development trends and open research issues are also outlined. All of those technologies have formed the foundation for the green computing that we know of today.

This book consists of eight chapters, five of which provide a summary of the tutorials and workshops organised as part of the cHiPSet Summer School: High-Performance Modelling and Simulation for Big Data Applications Cost Action on “New Trends in Modelling and Simulation in HPC Systems,” which was held in Bucharest (Romania) on September 21–23, 2016. As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems. Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. It is a valuable reference resource for those wanting to start working in HPC and big data systems, as well as for advanced researchers and practitioners.

The book is a collection of peer-reviewed scientific papers submitted by active researchers in the International Conference on Industry Interactive Innovation in Science, Engineering and Technology (I3SET 2016). The conference is a collective initiative of all departments and disciplines of JIS College of Engineering (an autonomous institution), Kalyani, West Bengal, India. The primary objective of the conference is to strengthen interdisciplinary research and encourage innovation in a demand-driven way as desired by the industry for escalating technology for mankind. A galaxy of academicians, professionals, scientists, industry people and researchers from different parts of the country and abroad shared and contributed their knowledge. The major areas of I3SET 2016 include nonconventional energy and advanced power systems; nanotechnology and applications; pattern recognition and machine intelligence; digital signal and image processing; modern instrumentation, control, robotics and automation; civil engineering and structural design; real-time and embedded systems, communication and devices; advanced optimization techniques; biotechnology, biomedical instrumentation and bioinformatics; and outcome based education.

This book presents new research contributions in the above-mentioned fields. Information and communication technologies (ICT) have an integral role in today’s society. Four major driving pillars in the field are computing, which nowadays enables data processing in unprecedented speeds, informatics, which derives information stemming for processed data to feed relevant applications, networking, which interconnects the various computing infrastructures and cybersecurity for addressing the growing concern for secure and lawful use of the ICT infrastructure and services. Its intended readership covers senior undergraduate and graduate students in Computer Science and Engineering and Electrical Engineering, as well as researchers, scientists, engineers, ICT managers, working in the relevant fields and industries.

Grid computing has emerged as one of the most promising computing paradigms of the new millennium! Achieving high performance Grid computing requires techniques to efficiently and adaptively allocate jobs and applications to available resources in a large scale, highly heterogenous and dynamic environment. This volume presents meta-heuristics approaches for Grid scheduling problems. Due to the complex nature of the problem, meta-heuristics are primary techniques for the design and implementation of efficient Grid schedulers. The volume brings new ideas, analysis, implementations and evaluation of meta-heuristic techniques for Grid scheduling, which make this volume novel in several aspects. The 14 chapters of this volume have identified several important formulations of the problem, which we believe will serve as a reference for the researchers in the Grid computing community. Important features include the detailed overview of the various novel metaheuristic scheduling approaches, excellent coverage of timely, advanced scheduling topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as well as engineers engaged in research, development and scheduling will find the comprehensive coverage of this book invaluable.

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Nature of Computation and Communication, ICTCC 2014, held in November 2014 in Ho Chi Minh City, Vietnam. The 34 revised full papers presented were carefully reviewed and selected from over 100 submissions. The papers cover formal methods for self-adaptive systems and discuss natural approaches and techniques for computation and communication.

This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.