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    跨云环境下任务调度综述

    Survey on Task Scheduling in Inter-Cloud Environment

    • 摘要: 随着云计算技术的不断发展,越来越多的企业和组织开始采用跨云的方式进行IT交付.跨云环境可以更有效地应对传统单云环境资源利用率低、资源受限以及供应商锁定等问题,并对云资源进行统一管理.由于跨云环境中资源具有异构性,导致跨云任务调度变得更为复杂.基于此,如何合理地调度用户任务并将其分配到最佳的跨云资源上执行,成为了跨云环境中需要解决的重要问题.拟从跨云环境的角度出发,探讨该环境下任务调度算法研究的进展及挑战.首先,结合跨云环境特征将云计算分为联盟云、多云环境并进行详细介绍,同时回顾已有的任务调度类型并分析其优缺点;其次,根据研究现状选取代表性文献对跨云环境下任务调度算法进行整理、分析;最后探讨了跨云环境下任务调度算法研究中的不足和未来的研究趋势,为跨云环境下任务调度算法的进一步研究提供了参考.

       

      Abstract: As cloud computing technology advances continuously, there are a growing number of enterprises and organizations choosing the inter-cloud approach to apply on IT delivery. Inter-cloud environments can efficiently solve problems such as low resource utilization, resource limitation, and vendor lock-in in traditional single-cloud environments, and manage cloud resources in an integrated model. Due to the heterogeneity of resources in the inter-cloud environment, which will complicate the scheduling of inter-cloud tasks. Based on the current status, how to logically schedule user tasks and allocate them to the most suitable inter-cloud resources for execution has developed to be an important issue to be solved in the inter-cloud environment. From the perspective of the inter-cloud environment, we discuss the progress and future challenges of research on the task of scheduling algorithms under this environment. Firstly, combined with the characteristics of an inter-cloud environment, cloud computing is divided into federated cloud and multi-cloud environments and introduced in detail. Meanwhile, the existing task scheduling types are reviewed and their advantages and disadvantages are analyzed. Secondly, based on the classification and current research procedure, representative documents are selected to analyze the algorithms for task scheduling on inter-cloud. Finally, shortcomings in research on algorithms for task scheduling in inter-cloud and future research trends are discussed, which provide a reference for further research on inter-cloud task scheduling.

       

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