Research On Resources Scheduling Method Base On Swarm Intelligence Optimal Algorithm In Cloud Computing Environment
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Research On Resources Scheduling Method Base On Swarm Intelligence Optimal Algorithm In Cloud Computing Environment
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Author : Hongwei Zhao
language : en
Publisher:
Release Date : 2017-06-14
Research On Resources Scheduling Method Base On Swarm Intelligence Optimal Algorithm In Cloud Computing Environment written by Hongwei Zhao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-14 with categories.
Swarm Intelligence For Cloud Computing
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Author : Indrajit Pan
language : en
Publisher: CRC Press
Release Date : 2020-07-19
Swarm Intelligence For Cloud Computing written by Indrajit Pan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-19 with Computers categories.
Swarm Intelligence in Cloud Computing is an invaluable treatise for researchers involved in delivering intelligent optimized solutions for reliable deployment, infrastructural stability, and security issues of cloud-based resources. Starting with a bird’s eye view on the prevalent state-of-the-art techniques, this book enriches the readers with the knowledge of evolving swarm intelligent optimized techniques for addressing different cloud computing issues including task scheduling, virtual machine allocation, load balancing and optimization, deadline handling, power-aware profiling, fault resilience, cost-effective design, and energy efficiency. The book offers comprehensive coverage of the most essential topics, including: Role of swarm intelligence on cloud computing services Cloud resource sharing strategies Cloud service provider selection Dynamic task and resource scheduling Data center resource management. Indrajit Pan is an Associate Professor in Information Technology of RCC Institute of Information Technology, India. He received his PhD from Indian Institute of Engineering Science and Technology, Shibpur, India. With an academic experience of 14 years, he has published around 40 research publications in different international journals, edited books, and conference proceedings. Mohamed Abd Elaziz is a Lecturer in the Mathematical Department of Zagazig University, Egypt. He received his PhD from the same university. He is the author of more than 100 articles. His research interests include machine learning, signal processing, image processing, cloud computing, and evolutionary algorithms. Siddhartha Bhattacharyya is a Professor in Computer Science and Engineering of Christ University, Bangalore. He received his PhD from Jadavpur University, India. He has published more than 230 research publications in international journals and conference proceedings in his 20 years of academic experience.
Certain Investigation On Improved Pso Algorithm For Workflow Scheduling In Cloud Computing Environments
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Author : Sadhasivam Narayanan
language : en
Publisher: Anchor Academic Publishing
Release Date : 2017-11-01
Certain Investigation On Improved Pso Algorithm For Workflow Scheduling In Cloud Computing Environments written by Sadhasivam Narayanan and has been published by Anchor Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-01 with Computers categories.
Cloud computing is a new prototype for enterprises which can effectively assist the execution of tasks. Task scheduling is a major constraint which greatly influences the performance of cloud computing environments. The cloud service providers and consumers have different objectives and requirements. For the moment, the load and availability of the resources vary dynamically with time. Therefore, in the cloud environment scheduling resources is a complicated problem. Moreover, task scheduling algorithm is a method by which tasks are allocated or matched to data center resources. All task scheduling problems in a cloud computing environment come under the class of combinatorial optimization problems which decide searching for an optimal solution in a finite set of potential solutions. For a combinatorial optimization problem in bounded time, exact algorithms always guarantee to find an optimal solution for every finite size instance. These kinds of problems are NP-Hard in nature. Moreover, for the large scale applications, an exact algorithm needs unexpected computation time which leads to an increase in computational burden. However, the absolutely perfect scheduling algorithm does not exist, because of conflicting scheduling objectives. Therefore, to overcome this constraint heuristic algorithms are proposed. In workflow scheduling problems, search space grows exponentially with the problem size. Heuristics optimization as a search method is useful in local search to find good solutions quickly in a restricted area. However, the heuristics optimization methods do not provide a suitable solution for the scheduling problem. Researchers have shown good performance of metaheuristic algorithms in a wide range of complex problems. In order to minimize the defined objective of task resource mapping, improved versions of Particle Swarm Optimization (PSO) are put in place to enhance scheduling performance with less computational burden. In recent years, PSO has been successfully applied to solve different kinds of problems. It is famous for its easy realization and fast convergence, while suffering from the possibility of early convergence to local optimums. In the proposed Improved Particle Swarm Optimization (IPSO) algorithm, whenever early convergence occurs, the original particle swarm would be considered the worst positions an individual particle and worst positions global particle the whole swarm have experienced.
Automated Workflow Scheduling In Self Adaptive Clouds
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Author : G. Kousalya
language : en
Publisher: Springer
Release Date : 2017-05-25
Automated Workflow Scheduling In Self Adaptive Clouds written by G. Kousalya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-25 with Computers categories.
This timely text/reference presents a comprehensive review of the workflow scheduling algorithms and approaches that are rapidly becoming essential for a range of software applications, due to their ability to efficiently leverage diverse and distributed cloud resources. Particular emphasis is placed on how workflow-based automation in software-defined cloud centers and hybrid IT systems can significantly enhance resource utilization and optimize energy efficiency. Topics and features: describes dynamic workflow and task scheduling techniques that work across multiple (on-premise and off-premise) clouds; presents simulation-based case studies, and details of real-time test bed-based implementations; offers analyses and comparisons of a broad selection of static and dynamic workflow algorithms; examines the considerations for the main parameters in projects limited by budget and time constraints; covers workflow management systems, workflow modeling and simulation techniques, and machine learning approaches for predictive workflow analytics. This must-read work provides invaluable practical insights from three subject matter experts in the cloud paradigm, which will empower IT practitioners and industry professionals in their daily assignments. Researchers and students interested in next-generation software-defined cloud environments will also greatly benefit from the material in the book.
Advances In Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2016-07-07
Advances In Swarm Intelligence written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-07 with Computers categories.
This two-volume set LNCS 9712 and LNCS 9713 constitutes the refereed proceedings of the 7th International Conference on Swarm Intelligence, ICSI 2016, held in Bali, Indonesia, in June 2016. The 130 revised regular papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in 22 cohesive sections covering major topics of swarm intelligence and related areas such as trend and models of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their applications; hybrid search optimization; particle swarm optimization; PSO applications; ant colony optimization; brain storm optimization; fireworks algorithms; multi-objective optimization; large-scale global optimization; biometrics; scheduling and planning; machine learning methods; clustering algorithm; classification; image classification and encryption; data mining; sensor networks and social networks; neural networks; swarm intelligence in management decision making and operations research; robot control; swarm robotics; intelligent energy and communications systems; and intelligent and interactive and tutoring systems.
Reliable And Intelligent Optimization In Multi Layered Cloud Computing Architectures
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Author : Madhusudhan H. S.
language : en
Publisher: CRC Press
Release Date : 2024-05-02
Reliable And Intelligent Optimization In Multi Layered Cloud Computing Architectures written by Madhusudhan H. S. and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-02 with Computers categories.
One of the major developments in the computing field has been cloud computing, which enables users to do complicated computations that local devices are unable to handle. The computing power and flexibility that have made the cloud so popular do not come without challenges. It is particularly challenging to decide which resources to use, even when they have the same configuration but different levels of performance because of the variable structure of the available resources. Cloud data centers can host millions of virtual machines, and where to locate these machines in the cloud is a difficult problem. Additionally, fulfilling optimization needs is a complex problem. Reliable and Intelligent Optimization in Multi-Layered Cloud Computing Architectures examines ways to meet these challenges. It discusses virtual machine placement techniques and task scheduling techniques that optimize resource utilization and minimize energy consumption of cloud data centers. Placement techniques presented can provide an optimal solution to the optimization problem using multiple objectives. The book focuses on basic design principles and analysis of virtual machine placement techniques and task allocation techniques. It also looks at virtual machine placement techniques that can improve quality-of-service (QoS) in service-oriented architecture (SOA) computing. The aims of virtual machine placement include minimizing energy usage, network traffic, economical cost, maximizing performance, and maximizing resource utilization. Other highlights of the book include: Improving QoS and resource efficiency Fault-tolerant and reliable resource optimization models A reactive fault tolerance method using checkpointing restart Cost and network-aware metaheuristics. Virtual machine scheduling and placement Electricity consumption in cloud data centers Written by leading experts and researchers, this book provides insights and techniques to those dedicated to improving cloud computing and its services.
Design And Analysis Of An Adjustable And Configurable Bio Inspired Heuristic Scheduling Technique For Cloud Based Systems
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Author : Ali Al Buhussain
language : en
Publisher:
Release Date : 2016
Design And Analysis Of An Adjustable And Configurable Bio Inspired Heuristic Scheduling Technique For Cloud Based Systems written by Ali Al Buhussain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Advanced Computing Techniques For Optimization In Cloud
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Author : H S Madhusudhan
language : en
Publisher: CRC Press
Release Date : 2024-09-11
Advanced Computing Techniques For Optimization In Cloud written by H S Madhusudhan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Computers categories.
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.
Resource Management In Distributed Systems
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Author : Anwesha Mukherjee
language : en
Publisher: Springer Nature
Release Date :
Resource Management In Distributed Systems written by Anwesha Mukherjee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Intelligent Computing And Networking
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Author : Valentina Emilia Balas
language : en
Publisher: Springer Nature
Release Date :
Intelligent Computing And Networking written by Valentina Emilia Balas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
