Comprehensive guide to the principles, algorithms, and techniques underlying resource management for clouds, big data, and sensor-based systems. Resource Management on Distributed Systems provides helpful guidance on resource management questions by describing algorithms and techniques for managing resources on parallel and distributed systems, including grids, clouds, and parallel processing-based platforms for big data analytics. The book introduces four general principles of resource management with a discussion of their impact on system performance, energy usage, and cost, and includes a set of exercises at the end of a chapter. To provide extensive coverage of the subject, the text includes chapters on sensors, autoscaling on clouds, complex event processing for streaming data, and data filtering techniques for big data systems. The book also covers results of applying the discussed techniques on simulated as well as real systems (including clouds and big data processing platforms), and techniques for handling errors associated with user predicted task execution times. Written by a highly qualified academic with significant research experience in the field, Resource Management on Distributed Systems includes information on sample topics such as: Attributes of parallel/distributed applications that have an intimate relationship with system behavior and performance, plus their related performance metrics. Handling a lack of a prior knowledge of local operating systems on individual nodes in a large system. Detection and management of complex events (that correspond to the occurrence of multiple raw events) on a platform for streaming analytics. Techniques for reducing data latency for multiple operator-based queries in an environment processing large textual documents. With comprehensive coverage of core topics in the field, Resource Management on Distributed Systems is a comprehensive guide to resource management in a single publication and is an essential read for professionals, researchers and students working with distributed systems.

Resource Management for Distributed Multimedia Systems addresses the problems and challenges of handling several continuous- media data streams in networked multimedia environments. The work demonstrates how resource management mechanisms can be integrated into a stream handling system. The resulting system includes functions for Quality of Service (QoS) calculations, scheduling, determination of resource requirements, and methods to reduce resource requirements. The work explains the following: a suitable system architecture and resource management scheme that allows for the provision and enforcement of QoS guarantee, resource scheduling mechanisms for CPU and buffer space, mechanisms to measure and collect resource requirements, methods to extend resource management to future scenarios by allowing the reservation of resources in advance and offering sealing mechanisms. . Resource Management for Distributed Multimedia Systems is a comprehensive view of resource management for a broad technical audience that includes computer scientists and engineers involved in developing multimedia applications.

In modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable and secure distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Failures may range from crashes to adversarial attacks by malicious processes. Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one topic, covering reliable broadcast, shared memory, consensus, and extensions of consensus. For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming". Its scope has been extended to include security against malicious actions by non-cooperating processes. This important domain has become widely known under the name "Byzantine fault-tolerance".

Serving as a flagship driver towards advance research in the area of Big Data platforms and applications, this book provides a platform for the dissemination of advanced topics of theory, research efforts and analysis, and implementation oriented on methods, techniques and performance evaluation. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These chapters discuss the research of members from the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). This volume is ideal as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp the key concerns and their potential solutions.

This unique volume explores cutting-edge management approaches to developing complex software that is efficient, scalable, sustainable, and suitable for distributed environments. Practical insights are offered by an international selection of pre-eminent authorities, including case studies, best practices, and balanced corporate analyses. Emphasis is placed on the use of the latest software technologies and frameworks for life-cycle methods, including the design, implementation and testing stages of software development. Topics and features: · Reviews approaches for reusability, cost and time estimation, and for functional size measurement of distributed software applications · Discusses the core characteristics of a large-scale defense system, and the design of software project management (SPM) as a service · Introduces the 3PR framework, research on crowdsourcing software development, and an innovative approach to modeling large-scale multi-agent software systems · Examines a system architecture for ambient assisted living, and an approach to cloud migration and management assessment · Describes a software error proneness mechanism, a novel Scrum process for use in the defense domain, and an ontology annotation for SPM in distributed environments · Investigates the benefits of agile project management for higher education institutions, and SPM that combines software and data engineering This important text/reference is essential reading for project managers and software engineers involved in developing software for distributed computing environments. Students and researchers interested in SPM technologies and frameworks will also find the work to be an invaluable resource. Prof. Zaigham Mahmood is a Senior Technology Consultant at Debesis Education UK and an Associate Lecturer (Research) at the University of Derby, UK. He also holds positions as Foreign Professor at NUST and IIU in Islamabad, Pakistan, and Professor Extraordinaire at the North West University Potchefstroom, South Africa.

Learning to build distributed systems is hard, especially if they are large scale. It's not that there is a lack of information out there. You can find academic papers, engineering blogs, and even books on the subject. The problem is that the available information is spread out all over the place, and if you were to put it on a spectrum from theory to practice, you would find a lot of material at the two ends but not much in the middle. That is why I decided to write a book that brings together the core theoretical and practical concepts of distributed systems so that you don't have to spend hours connecting the dots. This book will guide you through the fundamentals of large-scale distributed systems, with just enough details and external references to dive deeper. This is the guide I wished existed when I first started out, based on my experience building large distributed systems that scale to millions of requests per second and billions of devices. If you are a developer working on the backend of web or mobile applications (or would like to be!), this book is for you. When building distributed applications, you need to be familiar with the network stack, data consistency models, scalability and reliability patterns, observability best practices, and much more. Although you can build applications without knowing much of that, you will end up spending hours debugging and re-architecting them, learning hard lessons that you could have acquired in a much faster and less painful way. However, if you have several years of experience designing and building highly available and fault-tolerant applications that scale to millions of users, this book might not be for you. As an expert, you are likely looking for depth rather than breadth, and this book focuses more on the latter since it would be impossible to cover the field otherwise. The second edition is a complete rewrite of the previous edition. Every page of the first edition has been reviewed and where appropriate reworked, with new topics covered for the first time.