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ARMCO: Advanced topics in resource management for ubiquitous cloud computing: An adaptive approach

机译:ARMCO:无处不在的云计算资源管理中的高级主题:一种自适应方法

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摘要

Cloud Computing can be seen as one of the latest major evolution in computing offering unlimited possibility to use ICT in various domains: business, smart cities, medicine, environmental computing, mobile systems, design and implementation of cyber-infrastructures. The recent expansion of Cloud Systems has led to adapting resource management solutions for large number of wide distributed and heterogeneous datacenters. The adaptive methods used in this context are oriented on: self-stabilizing, self-organizing and autonomic systems; dynamic, adaptive and machine learning based distributed algorithms; fault tolerance, reliability, availability of distributed systems. The pay-per-use economic model of Cloud Computing comes with a new challenge: maximizing the profit for service providers, minimizing the total cost for customers and being friendly with the environment. This special issue presents advances in virtual machine assignment and placement, multi-objective and multi-constraints job scheduling, resource management in federated Clouds and in heterogeneous environments, dynamic topology for data distribution, workflow performance improvement, energy efficiency techniques and assurance of Service Level Agreements.
机译:云计算可以看作是计算领域的最新重大发展之一,它为在各种领域中使用ICT提供了无限的可能性:商业,智慧城市,医药,环境计算,移动系统,网络基础架构的设计和实施。云系统的最新扩展导致资源管理解决方案适用于大量的广泛分布式和异构数据中心。在这种情况下使用的自适应方法主要针对:自稳定,自组织和自主系统;基于动态,自适应和机器学习的分布式算法;容错性,可靠性,分布式系统的可用性。按需付费的云计算经济模型带来了新的挑战:最大化服务提供商的利润,最小化客户的总成本以及对环境友好。本期专刊介绍了虚拟机分配和放置,多目标和多约束作业调度,联合云和异构环境中的资源管理,数据分发的动态拓扑,工作流性能改进,能效技术和服务水平保证方面的进展。协议。

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