Download or read book Decentralized Multi Resource Allocation in Clouds written by Patrick Poullie and published by . This book was released on 2017-11-15 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud computing is omnipresent nowadays, as it allows for a fine-grained partitioning of data center resources and for flexibly providing access to these resources. This partitioning and provisioning is achieved by hosting several Virtual Machines (VM) on the same physical machine. In contrast to commercial clouds, the performance of VMs in a private cloud is not captured by Service Level Agreements, and thus, all VMs are treated as processes of equal importance. As users operate different numbers of VMs and these VMs utilize different amounts of physical resources, this equal treatment of VMs leads to users receiving unequal amounts of physical resources. This thesis improves this situation by defining an efficient approach to enforce fairness in private clouds.This thesis shows that cloud resources are best controlled by changing priorities of VMs to access physical resources of their host and that no assumptions on utility functions can be made during this step. The premiss of this thesis that it is fair to constrain greedy users in favor of less greedy users requires a metric that quantifies the greediness of users based on their multi-resource self-servings from a shared resource pool. Thus, the Greediness Metric is developed based on a questionnaire among more than 600 participants on the intuitive understanding of greediness and fairness. The Greediness Metric is refined to define cloud fairness in a way that outperforms all existing cloud fairness definitions. To demonstrate the practical applicability of this cloud fairness definition, OpenStack is extended by an according service. The processing overhead of this service is evaluated and it is proven that it enforces fairness among users by coordinating the VM prioritization on hosts.

Download or read book Resource Management in Utility and Cloud Computing written by Han Zhao and published by Springer Science & Business Media. This book was released on 2013-10-17 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief reviews the existing market-oriented strategies for economically managing resource allocation in distributed systems. It describes three new schemes that address cost-efficiency, user incentives, and allocation fairness with regard to different scheduling contexts. The first scheme, taking the Amazon EC2TM market as a case of study, investigates the optimal resource rental planning models based on linear integer programming and stochastic optimization techniques. This model is useful to explore the interaction between the cloud infrastructure provider and the cloud resource customers. The second scheme targets a free-trade resource market, studying the interactions amongst multiple rational resource traders. Leveraging an optimization framework from AI, this scheme examines the spontaneous exchange of resources among multiple resource owners. Finally, the third scheme describes an experimental market-oriented resource sharing platform inspired by eBay's transaction model. The study presented in this book sheds light on economic models and their implication to the utility-oriented scheduling problems.

Download or read book Dynamic Resource Allocation in Embedded High Performance and Cloud Computing written by Leando Soares Indrusiak and published by CRC Press. This book was released on 2022-09-01 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale manycore systems are notoriously hard to optimise. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude). Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonise the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements. Technical topics presented in the book include: • Load and Resource Models• Admission Control• Feedback-based Allocation and Optimisation• Search-based Allocation Heuristics• Distributed Allocation based on Swarm Intelligence• Value-Based AllocationEach of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip manycore processors, grids and private cloud environments.

Download or read book Multicloud Resource Allocation written by Hao Zhuang and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Mots-clés de l'auteur: mutlicloud resource allocation ; decentralized cloud ; multicloud storage system ; multicloud optimization ; data sharing ; small data center ; data transfer ; information leakage ; system attackability ; data summarization ; social context.

Download or read book Operationalizing Multi Cloud Environments written by Rajganesh Nagarajan and published by Springer Nature. This book was released on 2021-09-17 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various aspects of the multi-cloud paradigm. The initial portion of the book focuses on the motivations for the industry to embrace a multi-cloud option and the distinct business, technology, and user cases of multi-cloud implementations. The middle part of the book explains the challenges of setting up and sustaining multi-cloud environments. The latter portion focuses on the next-generation technologies and tools along with multi-cloud platforms, processes, patterns, and practices. The final segment of the book is dedicated for cloud brokerage systems. The various traits and tenets of cloud brokerage services especially for accomplishing cloud intermediation, integration, orchestration, governance, security, management, configuration, etc. are explained in detail. The book also clearly articulates how to have intelligent brokers.

Download or read book Resource Allocation and Scheduling in Heterogeneous Cloud Environments written by Gunho Lee and published by . This book was released on 2012 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, there has been a dramatic increase in the popularity of cloud computing systems that rent computing resources on-demand, bill on a pay-as-you-go basis, and multiplex many users on the same physical infrastructure. These cloud computing environments provide an illusion of infinite computing resources to cloud users so that they can increase or decrease their resource consumption rate according to the demands. At the same time, the cloud environment poses a number of challenges. Two players in cloud computing environments, cloud providers and cloud users, pursue different goals; providers want to maximize revenue by achieving high resource utilization, while users want to minimize expenses while meeting their performance requirements. However, it is difficult to allocate resources in a mutually optimal way due to the lack of information sharing between them. Moreover, ever-increasing heterogeneity and variability of the environment poses even harder challenges for both parties. In this thesis, we address "the cloud resource management problem", which is to allocate and schedule computing resources in a way that providers achieve high resource utilization and users meet their applications' performance requirements with minimum expenditure. We approach the problem from various aspects, using MapReduce as our target application. From provider's perspective, we propose a topology-aware resource placement solution to overcome the lack of information sharing between providers and users. From user's point of view, we present a resource allocation scheme to maintain a pool of leased resources in a cost-effective way and a progress share-based job scheduling algorithm that achieves high performance and fairness simultaneously in a heterogeneous cloud environment. To deal with variability in resource capacity and application performance in the Cloud, we develop a method to predict the job completion time distribution that is applicable to making sophisticated trade-off decisions in resource allocation and scheduling. Our evaluation shows that these methods can improve efficiency and effectiveness of cloud computing systems.

Download or read book Adaptive Resource Management and Scheduling for Cloud Computing written by Florin Pop and published by Springer. This book was released on 2014-11-25 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the First International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2014, held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2014, in Paris, France, in July 2014. The 14 revised full papers (including 2 invited talks) were carefully reviewed and selected from 29 submissions and cover topics such as scheduling methods and algorithms, services and applications, fundamental models for resource management in the cloud.

Download or read book Optimized Cloud Resource Management and Scheduling written by Wenhong Dr. Tian and published by Morgan Kaufmann. This book was released on 2014-10-15 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimized Cloud Resource Management and Scheduling identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It serves as a valuable reference for systems architects, practitioners, developers, researchers and graduate level students. Explains how to optimally model and schedule computing resources in cloud computing Provides in depth quality analysis of different load-balance and energy-efficient scheduling algorithms for cloud data centers and Hadoop clusters Introduces real-world applications, including business, scientific and related case studies Discusses different cloud platforms with real test-bed and simulation tools

Download or read book Resource Allocation Based on Predictive Load Balancing Approach in Multi Cloud Environment written by S. Sindhura and published by . This book was released on 2020 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud computing gives a support to purchasers to lessen their internal establishment, and for providers to extend wages, using their own specific system. The best possible burden adjusting and dynamic asset provisioning improves cloud execution and draws in the cloud clients. In this paper, we propose a mechanized asset provisioning calculation, Speculation asset provisioning, inciting load adjusting through theoretical methodology in asset provisioning. As an endeavor to measure asset portion we utilize two level versatile expectation component to check the computational examples of past asset distribution to the future necessity. The structure ensures reasonable assets required for the application, by avoiding over or under-provisioning of asset and supports vitality effectiveness in asset distribution. We use estimation system to address the fluctuation in the verifiable information to adjust the theory overhead. We have passed on our proposed work in an open source cloud structure and differentiated our results and other AI draws near. Our Experimental outcomes show versatile asset designation over client driven help the executives under the quickly changing necessities of cloud computing.

Download or read book Autonomic Computing in Cloud Resource Management in Industry 4 0 written by Tanupriya Choudhury and published by Springer Nature. This book was released on 2021-09-05 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the next generation of industry—Industry 4.0—and how it holds the promise of increased flexibility in manufacturing, along with automation, better quality, and improved productivity. The authors discuss how it thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. The authors posit that intelligent cloud services and resource sharing play an important role in Industry 4.0 anticipated Fourth Industrial Revolution. This book serves the different issues and challenges in cloud resource management CRM techniques with proper propped solution for IT organizations. The book features chapters based on the characteristics of autonomic computing with its applicability in CRM. Each chapter features the techniques and analysis of each mechanism to make better resource management in cloud.

Download or read book Dynamic Resource Allocation in Embedded High Performance and Cloud Computing written by Leando Soares Indrusiak and published by River Publishers. This book was released on 2016-10-31 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale manycore systems are notoriously hard to optimise. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude). Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonise the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements. Technical topics presented in the book include: Load and Resource ModelsAdmission ControlFeedback-based Allocation and OptimisationSearch-based Allocation HeuristicsDistributed Allocation based on Swarm IntelligenceValue-Based Allocation Each of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip manycore processors, grids and private cloud environments.

Download or read book Energy Efficient Resource Allocation in Cloud Computing written by Dilip Kumar and published by LAP Lambert Academic Publishing. This book was released on 2014-06-30 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: These heuristic algorithms operate in two phases, selection of task from the task pool, followed by selection of cloud resource. A set of ten greedy heuristics for resource allocation using the greedy paradigm has been used, that operates in two stages. At each stage a particular input is selected through a selection procedure. Then a decision is made regarding the selected input, whether to include it into the partially constructed optimal solution. The selection procedure can be realized using a 2-phase heuristic. In particular, we have used 'FcfsRand', 'FcfsRr', 'FcfsMin', 'FcfsMax', 'MinMin', 'MedianMin', 'MaxMin', 'MinMax', 'MedianMax', and 'MaxMax'. The simulation results indicate in the favor of MaxMax. The novel genetic algorithm framework has been proposed for task scheduling to minimize the energy consumption in cloud computing infrastructure. The performance of the proposed GA resource allocation strategy has been compared with Random and Round Robin scheduling.

Download or read book Multi Cloud Handbook for Developers written by Subash Natarajan and published by Packt Publishing Ltd. This book was released on 2024-02-29 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore proven techniques and best practices for designing, deploying, and managing cloud-native applications in multi-cloud environments with the help of real-world examples, success stories, and emerging technologies Key Features Discover optimal solutions in multi-cloud environments using AWS, Azure, and GCP tools and technologies Excel in designing, developing, and securing cloud-native apps with Docker, Kubernetes, and Istio Learn design patterns, cost optimization, best practices, and pitfalls to avoid in multi-cloud apps Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionUnleash the power of cloud computing with Multi-Cloud Handbook for Developers, your guide to mastering the nuances of cloud-native and multi-cloud, covering practical strategies for design, development, and management. Explore the essential concepts, challenges, and methodologies critical for navigating the complex landscape of modern cloud computing. Using core architectural and design principles (such as microservices and 12-factor architecture) and advanced strategies (such as distributed application design patterns, domain-driven design (DDD), and API-first strategies), you’ll learn how to build portable and efficient apps across various cloud platforms. You’ll understand how to leverage Infrastructure as Code (IaC), continuous integration and deployment (CI/CD), GitOps, and DevOps practices, along with containerization and orchestration techniques using Docker and Kubernetes. You’ll also get to grips with data, security, compliance, and cloud cost management strategies in multi-cloud environments. With real-world case studies, best practices, and insights into future trends, this book will equip you with the skills to develop, manage, troubleshoot, and innovate cloud-native applications across diverse cloud platforms, positioning you at the forefront of the cloud computing revolution.What you will learn Understand the core structures and implications of cloud-native and multi-cloud apps Explore key principles and patterns to build agile, scalable, and future-proof apps Master cloud-native essentials: service mesh, DDD, and API-centric approaches Implement deployment pipelines with advanced IaC, CI/CD, DevSecOps, and GitOps techniques Manage and monitor data, security, compliance, and identity access in multi-cloud scenarios Optimize your cloud costs with shift-left and FinOps practices Get ready for the future of cloud-native and multi-cloud technology Who this book is for Ideal for cloud-native and cloud developers, platform engineers, software architects, and IT professionals focused on building and managing cloud-native applications in multi-cloud environments, this book is an indispensable guide for students and researchers seeking insights into cloud-native concepts and multi-cloud architectures. A basic understanding of cloud computing, contemporary software development, system design, and cloud platforms such as AWS, Azure, and GCP, will prove useful.

Download or read book Resource Management in Distributed Systems written by Anwesha Mukherjee and published by Springer Nature. This book was released on with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Computing Techniques for Optimization in Cloud written by H S Madhusudhan and published by CRC Press. This book was released on 2024-09-11 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques. Focuses on virtual machine placement and migration techniques for cloud data centers Presents the role of machine learning and metaheuristic approaches for optimisation in cloud computing services Includes application of placement techniques for quality of service, performance, and reliability improvement Explores data center resource management, load balancing and orchestration using machine learning techniques Analyses dynamic and scalable resource scheduling with a focus on resource management The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.

Download or read book A Cloud Computing Framework For Sharing Of Cloud Resources And Attacks Information Amongst Cloud Networks written by Abdul Waqas and published by IIUM PRESS. This book was released on 2017-03-13 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud computing has emerged as a new paradigm for hosting and delivering computing resources over the Internet. This research proposed a cross-cloud communication framework (C3F) for enabling communication among clouds with minimal management burden. Further, it enabled the borrowing and lending of resources among clouds whenever required to fulfil the client requests. It also facilitated to share the information of attacks and intruding entities to cater with same attacks on different clouds. The framework was deployed using web-based prototype development to test and validate the cross-cloud communication. The prototype was developed using open source technologies. Moreover, algorithms were developed using low level description technique for the processes of resource borrowing and lending and, sharing of attacks information. The algorithms were analyzed to test their asymptotic running time complexity, and programmed in accordance with prototype of the study for testing and validation. The results showed high success rate of 94.4% for sharing of resources among clouds with mean allocation time of 12 microseconds. It was observed that 94.4% of the time clients’ requests were fulfilled successfully after borrowing the resources from cloud network. An average of 100% results were collected for protecting multiple clouds from same attack by sharing the attacks and intruders information among clouds in different situations. It is therefore concluded that cross-cloud communication framework can benefit for sharing of resources and attacks information among clouds for efficient resource management and allocation and, protection against same attacks at different clouds.

Download or read book Adaptive Resource Management and Scheduling for Cloud Computing written by Florin Pop and published by Springer. This book was released on 2016-01-07 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2015, held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2015, in Donostia-San Sebastián, Spain, in July 2015. The 12 revised full papers, including 1 invited paper, were carefully reviewed and selected from 24 submissions. The papers have identified several important aspects of the problem addressed by ARMS-CC: self-* and autonomous cloud systems, cloud quality management and service level agreement (SLA), scalable computing, mobile cloud computing, cloud computing techniques for big data, high performance cloud computing, resource management in big data platforms, scheduling algorithms for big data processing, cloud composition, federation, bridging, and bursting, cloud resource virtualization and composition, load-balancing and co-allocation, fault tolerance, reliability, and availability of cloud systems.