Download or read book Centralized and Decentralized Methods of Efficient Resource Allocation in Cloud Computing written by Su Seon Yang and published by . This book was released on 2016 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resource allocation in cloud computing determines the allocation of computer and network resources of service providers to service requests of cloud users for meeting the cloud users' service requirements. The efficient and effective resource allocation determines the success of cloud computing. However, it is challenging to satisfy objectives of all service providers and all cloud users in an unpredictable environment with dynamic workload, large shared resources and complex policies to manage them. Many studies propose to use centralized algorithms for achieving optimal solutions for resource allocation. However, the centralized algorithms may encounter the scalability problem to handle a large number of service requests in a realistically satisfactory time. Hence, this dissertation presents two studies. One study develops and tests heuristics of centralized resource allocation to produce near-optimal solutions in a scalable manner. Another study looks into decentralized methods of performing resource allocation. The first part of this dissertation defines the resource allocation problem as a centralized optimization problem in Mixed Integer Programming (MIP) and obtains the optimal solutions for various resource-service problem scenarios. Based on the analysis of the optimal solutions, various heuristics are designed for efficient resource allocation. Extended experiments are conducted with larger numbers of user requests and service providers for performance evaluation of the resource allocation heuristics. Experimental results of the resource allocation heuristics show the comparable performance of the heuristics to the optimal solutions from solving the optimization problem. Moreover, the resource allocation heuristics demonstrate better computational efficiency and thus scalability than solving the optimization problem.The second part of this dissertation looks into elements of service provider-user coordination first in the formulation of the centralized resource allocation problem in MIP and then in the formulation of the optimization problem in a decentralized manner for various problem cases. By examining differences between the centralized, optimal solutions and the decentralized solutions for those problem cases, the analysis of how the decentralized service provider-user coordination breaks down the optimal solutions is performed. Based on the analysis, strategies of decentralized service provider-user coordination are developed.
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 Decentralized Algorithms for Resource Allocation in Mobile Cloud Computing Systems written by Sladana Josilo and published by . This book was released on 2018 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Techniques for Decentralized and Dynamic Resource Allocation written by Lorenzo Ferrari and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis investigates three different resource allocation problems, aiming to achieve two common goals: i) adaptivity to a fast-changing environment, ii) distribution of the computation tasks to achieve a favorable solution. The motivation for this work relies on the modern-era proliferation of sensors and devices, in the Data Acquisition Systems (DAS) layer of the Internet of Things (IoT) architecture. To avoid congestion and enable low-latency services, limits have to be imposed on the amount of decisions that can be centralized (i.e. solved in the "cloud") and/or amount of control information that devices can exchange. This has been the motivation to develop i) a lightweight PHY Layer protocol for time synchronization and scheduling in Wireless Sensor Networks (WSNs), ii) an adaptive receiver that enables Sub-Nyquist sampling, for efficient spectrum sensing at high frequencies, and iii) an SDN-scheme for resource-sharing across different technologies and operators, to harmoniously and holistically respond to fluctuations in demands at the eNodeB' s layer. The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol. The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized. The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA). The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics. While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints. The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).
Download or read book Decentralized Resources Allocation Mechanisms in Networks written by Tudor Mihai Stoenescu and published by . This book was released on 2004 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cognitive Analytics and Reinforcement Learning written by Elakkiya R. and published by John Wiley & Sons. This book was released on 2024-04-10 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: COGNITIVE ANALYTICS AND REINFORCEMENT LEARNING The combination of cognitive analytics and reinforcement learning is a transformational force in the field of modern technological breakthroughs, reshaping the decision-making, problem-solving, and innovation landscape; this book offers an examination of the profound overlap between these two fields and illuminates its significant consequences for business, academia, and research. Cognitive analytics and reinforcement learning are pivotal branches of artificial intelligence. They have garnered increased attention in the research field and industry domain on how humans perceive, interpret, and respond to information. Cognitive science allows us to understand data, mimic human cognitive processes, and make informed decisions to identify patterns and adapt to dynamic situations. The process enhances the capabilities of various applications. Readers will uncover the latest advancements in AI and machine learning, gaining valuable insights into how these technologies are revolutionizing various industries, including transforming healthcare by enabling smarter diagnosis and treatment decisions, enhancing the efficiency of smart cities through dynamic decision control, optimizing debt collection strategies, predicting optimal moves in complex scenarios like chess, and much more. With a focus on bridging the gap between theory and practice, this book serves as an invaluable resource for researchers and industry professionals seeking to leverage cognitive analytics and reinforcement learning to drive innovation and solve complex problems. The book’s real strength lies in bridging the gap between theoretical knowledge and practical implementation. It offers a rich tapestry of use cases and examples. Whether you are a student looking to gain a deeper understanding of these cutting-edge technologies, an AI practitioner seeking innovative solutions for your projects, or an industry leader interested in the strategic applications of AI, this book offers a treasure trove of insights and knowledge to help you navigate the complex and exciting world of cognitive analytics and reinforcement learning. Audience The book caters to a diverse audience that spans academic researchers, AI practitioners, data scientists, industry leaders, tech enthusiasts, and educators who associate with artificial intelligence, data analytics, and cognitive sciences.
Download or read book Algorithmic Aspects of Cloud Computing written by Ioannis Chatzigiannakis and published by Springer Nature. This book was released on 2023-12-13 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised selected papers from the 8th International Symposium on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2023, held in Amsterdam, The Netherlands, on September 5, 2023. The 13 full papers included in this book were carefully reviewed and selected from 24 submissions. They focus on algorithmic aspects of computing and data management in modern cloud-based systems interpreted broadly so as to include edge- and fog-based systems, cloudlets, cloud micro-services, virtualization environments, decentralized systems, as well as dynamic networks.
Download or read book ICIDSSD 2020 written by M. Afshar Alam and published by European Alliance for Innovation. This book was released on 2021-03-03 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on ICT for Digital, Smart, and Sustainable Development (ICIDSSD’20) aims to provide an annual platform for the researchers, academicians, and professionals from across the world. ICIDSSD’20, held at Jamia Hamdard, New Delhi, India, is the second international conference of this series of conferences to be held annually. The conference majorly focuses on the recent developments in the areas relating to Information and Communication Technologies and contributing to Sustainable Development. ICIDSSD’20 has attracted research papers pertaining to an array of exciting research areas. The selected papers cover a wide range of topics including but not limited to Sustainable Development, Green Computing, Smart City, Artificial Intelligence, Big Data, Machine Learning, Cloud Computing, IoT, ANN, Cyber Security, and Data Science. Papers have primarily been judged on originality, presentation, relevance, and quality of work. Papers that clearly demonstrate results have been preferred. We thank our esteemed authors for having shown confidence in us and entrusting us with the publication of their research papers. The success of the conference would not have been possible without the submission of their quality research works. We thank the members of the International Scientific Advisory Committee, Technical Program Committee and members of all the other committees for their advice, guidance, and efforts. Also, we are grateful to our technical partners and sponsors, viz. HNF, EAI, ISTE, AICTE, IIC, CSI, IETE, Department of Higher Education, MHRD and DST for sponsorship and assistance.
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 Centralised Or Decentralised written by Paula Jarzabkowski and published by . This book was released on 2001 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Resource Allocation in Decentralized Systems with Strategic Agents written by Ali Kakhbod and published by Springer Science & Business Media. This book was released on 2013-01-24 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents a significant contribution to decentralized resource allocation problems with strategic agents. The study focused on three classes of problems arising in communication networks. (C1). Unicast service provisioning in wired networks. (C2). Multi-rate multicast service provisioning in wired networks. (C3). Power allocation and spectrum sharing in multi-user multi-channel wireless communication systems. Problems in (C1) are market problems; problems in (C2) are a combination of markets and public goods; problems in (C3) are public goods. Dr. Kakhbod developed game forms/mechanisms for unicast and multi-rate multicast service provisioning that possess specific properties. First, the allocations corresponding to all Nash equilibria (NE) of the games induced by the mechanisms are optimal solutions of the corresponding centralized allocation problems, where the objective is the maximization of the sum of the agents' utilities. Second, the strategic agents voluntarily participate in the allocation process. Third, the budget is balanced at the allocations corresponding to all NE of the game induced by the mechanism as well as at all other feasible allocations. For the power allocation and spectrum sharing problem, he developed a game form that possesses the second and third properties as detailed above along with a fourth property: the allocations corresponding to all NE of the game induced by the mechanism are Pareto optimal. The thesis contributes to the state of the art of mechanism design theory. In particular, designing efficient mechanisms for the class of problems that are a combination of markets and public goods, for the first time, have been addressed in this thesis. The exposition, although highly rigorous and technical, is elegant and insightful which makes this thesis work easily accessible to those just entering this field and will also be much appreciated by experts in the field.
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 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 Efficient Auction Games written by Zhongjing Ma and published by Springer Nature. This book was released on 2020-02-13 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the design of efficient & dynamic methods to allocate divisible resources under various auction mechanisms, discussing their applications in power & microgrid systems and the V2G & EV charging coordination problems in smart grids. It describes the design of dynamic methods for single-sided and double-sided auction games and presents a number of simulation cases verifying the performances of the proposed algorithms in terms of efficiency, convergence and computational complexity. Further, it explores the performances of certain auction mechanisms in a hierarchical structure and with large-scale agents, as well as the auction mechanisms for the efficient allocation of multi-type resources. Lastly, it generalizes the main and demonstrates their application in smart grids. This book is a valuable resource for researchers, engineers, and graduate students in the fields of optimization, game theory, auction mechanisms and smart grids interested in designing dynamic auction mechanisms to implement optimal allocation of divisible resources, especially electricity and other types of energy in smart grids.
Download or read book Resource Management and Efficiency in Cloud Computing Environments written by Turuk, Ashok Kumar and published by IGI Global. This book was released on 2016-11-08 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today’s advancements in technology have brought about a new era of speed and simplicity for consumers and businesses. Due to these new benefits, the possibilities of universal connectivity, storage and computation are made tangible, thus leading the way to new Internet-of Things solutions. Resource Management and Efficiency in Cloud Computing Environments is an authoritative reference source for the latest scholarly research on the emerging trends of cloud computing and reveals the benefits cloud paths provide to consumers. Featuring coverage across a range of relevant perspectives and topics, such as big data, cloud security, and utility computing, this publication is an essential source for researchers, students and professionals seeking current research on the organization and productivity of cloud computing environments.
Download or read book Online Mechanisms for Dynamic Resource Provisioning in Cloud Computing written by Weijie Shi and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Online Mechanisms for Dynamic Resource Provisioning in Cloud Computing" by Weijie, Shi, 施維捷, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Auction mechanisms, which have recently attracted substantial attention, are efficient approaches to resource allocation and pricing in cloud computing. In contrast to fixed price policy, auction mechanism can adapt to realtime demand/supply changes, achieving maximal market efficiency and provider revenue. Cloud users arrive in an online fashion, requiring the provider to provision resources on demand, which complicates the design of the mechanism compared with online mechanisms. Although some online mechanisms have been proposed in this field, existing solutions are still not completely satisfactory, especially for heterogeneous types of Virtual Machines (VM) and bandwidth resources. In this thesis, we propose efficient online mechanisms for computational and communication resources provisioning, using techniques of primal-dual optimization and auction theory. We first investigate the online auctions for heterogeneous types of VMs with and without user budget, respectively. For the model without user budget, we propose a truthful online mechanism that timely responds to incoming users' demands and makes dynamic allocation decisions, while guaranteeing system efficiency, using the pricing curve technique. For the model with user budget constraint, we use primal-dual technique to decompose the online combinatorial optimization into a series of independent single-user optimization problems, and solve the single-user problem with randomized auctions. In both solutions, our mechanisms provision different types of VMs dynamically, adjusting the number of instances of VMs to realtime user demand. Next, we turn to bandwidth resource allocation in cloud computing. We novelly exploit the Shapley value in the auction mechanism design, and present the first dynamic pricing mechanism for inter-datacenter on-demand bandwidth. Our auctions, including both online and online version, are expressive enough to accept bids as a at bandwidth rate plus a time duration, or a data volume with a transfer deadline, and achieve approximately efficiency in social welfare. Finally, we combine the computational resources with the communication resources under a unified framework, and propose the first online algorithm for dynamic Virtual Cluster (VC) provisioning and pricing, which optimally places VCs, routes inter-VM traffic and charges a market-driven price for each VC. We use the pricing-curve method to design a social welfare maximizing auction, and then convert it to a revenue maximizing online auction using randomized payment boosting technique. Through theoretical analysis and trace-driven simulations, we rigorously examine the efficiency of our mechanisms comparing with both the theoretical optima and existing solutions. Subjects: Resource allocation - Mathematical models Cloud computing
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:
