Metaheuristics for Scheduling in Distributed Computing Environments


Book Description

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.




Masters Theses in the Pure and Applied Sciences


Book Description

Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS) * at Purdue University in 1 957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dissemination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all con cerned if the printing and distribution of the volumes were handled by an interna tional publishing house to assure improved service and broader dissemination. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Cor poration of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 28 (thesis year 1 983) a total of 10,661 theses titles from 26 Canadian and 197 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this important annual reference work. While Volume 28 reports theses submitted in-1983, on occasion, certain univer sities do report theses submitted in previous years but not reported at the time.




A FRAMEWORK FOR SCALABLE DISTRIBUTED JOB PROCESSING WITH DYNAMIC LOAD BALANCING USING DECENTRALIZED APPROACH


Book Description

A distributed system consists of many heterogeneous processors with different processing power and all processors are interconnected with a communication channel. In such a system, if some processors are less loaded or idle and others are heavily loaded, the system performance will be reduced drastically. System performance can be improved by using proper load balancing [1, 4]. The aim of load balancing is to improve the performance measures and reduce the overall completion time and cost




Proceedings


Book Description




Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions


Book Description

This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.




Distributed Systems


Book Description

This second edition of Distributed Systems, Principles & Paradigms, covers the principles, advanced concepts, and technologies of distributed systems in detail, including: communication, replication, fault tolerance, and security. Intended for use in a senior/graduate level distributed systems course or by professionals, this text systematically shows how distributed systems are designed and implemented in real systems.




Computational Intelligence and Blockchain in Complex Systems


Book Description

Computational Intelligence and Blockchain in Complex Systems provides readers with a guide to understanding the dynamics of AI, Machine Learning, and Computational Intelligence in Blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. The book examines the role of Computational Intelligence and Machine Learning in the development of algorithms to deploy Blockchain technology across a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and supply chain. The authors cover the unique and developing intersection between cyber security and Blockchain in modern networks, as well as in-depth studies on cyber security challenges and multidisciplinary methods in modern Blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in Blockchain security aspects for hashing, coding, and decoding. Computational Intelligence and Blockchain in Complex Systems provides readers with the most in-depth technical guide to the intersection of Computational Intelligence and Blockchain, two of the most important technologies for the development of next generation complex systems. - Covers the research issues and concepts of machine learning technology in blockchain - Provides in-depth information about handling and managing personal data by machine learning methods in blockchain - Helps readers understand the links between computational intelligence, blockchain, complex systems, and developing secure applications in multidisciplinary sectors




Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing


Book Description

Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. The Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing is a vital reference source that provides valuable insight into current and emergent research occurring within the field of distributed computing. It also presents architectures and service frameworks to achieve highly integrated distributed systems and solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting a range of topics such as data sharing, wireless sensor networks, and scalability, this multi-volume book is ideally designed for system administrators, integrators, designers, developers, researchers, academicians, and students.




Computational Science - ICCS 2003


Book Description

The four-volume set LNCS 2657, LNCS 2658, LNCS 2659, and LNCS 2660 constitutes the refereed proceedings of the Third International Conference on Computational Science, ICCS 2003, held concurrently in Melbourne, Australia and in St. Petersburg, Russia in June 2003. The four volumes present more than 460 reviewed contributed and invited papers and span the whole range of computational science, from foundational issues in computer science and algorithmic mathematics to advanced applications in virtually all application fields making use of computational techniques. These proceedings give a unique account of recent results in the field.




Parallel and Distributed Computing


Book Description

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing.