Abstract:

With the rapid growth of application computing demand, heterogeneous computing resources continue to increase, task scheduling has become an important research problem in the field of cloud computing. Task scheduling is responsible for matching user tasks to appropriate virtual computing resources. The quality of the algorithm will directly affect the response time, makespan, energy consumption, cost, resource utilization and a series of performance indexes that are closely related to the economic interests of users and cloud service providers. This paper summarizes and discusses the research progress of task scheduling algorithm based on the characteristics of different cloud environments, aiming at independent task and scientific workflow. Firstly, it reviews the existing task scheduling types, scheduling mechanisms and their advantages and disadvantages. Secondly, task scheduling characteristics under single cloud environment, and inter-cloud environment such as hybrid cloud, multi-cloud and federated cloud are summarized, and schedule methods, optimization objectives, pros and cons of some typical relevant literatures are described. On this basis, the research status of task scheduling under various environments is discussed. Then, the scheduling optimization methods used in various environments are further sorted out to clarify their scope of use. Finally, it summarizes the whole paper and points out that it is necessary to pay more attention to the research of task scheduling in computing data intensive applications under inter-cloud environment.

Key words: cloud computing, task scheduling, single cloud, inter-cloud, independent tasks, workflow

摘要：

随着应用程序计算需求的快速增长，异构计算资源不断地增多，任务调度成为云计算领域中重要的研究问题。任务调度负责将用户任务匹配给合适的虚拟计算资源，算法的优劣将直接影响响应时间、最大完工时间、能耗、成本、资源利用率等一系列与用户和云服务供应商经济利益密切相关的性能指标大小。针对独立任务和科学工作流这两类云环境主流任务，结合不同云环境特征对任务调度算法研究进展进行综述和讨论。回顾梳理已有的任务调度类型、调度机制及其优缺点；归纳单云环境和混合云、多云及联盟云等跨云环境下任务调度特征，并对部分相关典型文献的使用方法、优化目标、优缺点等方面进行阐述，在此基础上讨论各个环境下任务调度研究现状；进一步对各类环境下文献使用的调度优化方法进行梳理，明确其使用范围；总结并指出需要对计算数据密集型应用在跨云环境下的任务调度研究进行重点关注。

关键词: 云计算, 任务调度, 单云, 跨云, 独立任务, 科学工作流