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基于启发式算法的混合云工作流调度算法
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Abstract:
伴随着“互联网+”技术的飞速发展，世界各地的网络环境越来越好，通过云计算技术操作异地计算资源的情况也越来越多。其中当本地资源不足时，私有云、公有云混合的混合云方案被各大企业广泛应用，本文针对混合云环境中的工作流任务调度问题，研究在满足任务截止期约束的同时使私有云利润最大化，节约企业成本。在私有云环境中，本文提出了一种优化的蚁群算法(Ant Colony Optimization Workflow Scheduling, ACOWS)用于工作流在用户指定的期限内完成任务的执行。在此基础上提出混合云下的动态多工作流调度算法(Hybrid Cloud Deadline-Constrained Cost Workflows Scheduling, HCDCW)，该算法将优先在私有云中调度执行，当任务执行时间超出任务截止期约束时，使用公有云调度部分工作流。在实验阶段，利用WorkflowSim仿真平台对算法进行了验证，实验结果表明在不同截止期，该调度算法相比于传统混合云工作流调度算法能有效的帮助企业在使用混合云过程中降低租用公有云的费用成本，并获得更快的执行时间。
With the rapid development of the “Internet+” technology, the network environment around the world is getting better and better, and there are more and more cases of operating remote computing resources through cloud computing technology. Among them, when the local resources are in-sufficient, the hybrid cloud solution of private cloud and public cloud is widely used by major enterprises. This article focuses on the workflow task scheduling problem in the hybrid cloud environment, and researches to maximize private cloud profits while meeting task deadline constraints, to save business costs. In a private cloud environment, an optimized Ant Colony Optimization Work- flow Scheduling (ACOWS) is proposed in the article for the workflow to complete the execution of tasks within the time limit specified by the user. On this basis, a dynamic multi-workflow scheduling algorithm (Hybrid Cloud Deadline-Constrained Cost Workflows Scheduling, HCDCW) under the hybrid cloud is proposed. The algorithm will be scheduled and executed in the private cloud first. When the task execution time exceeds the task deadline constraint, use the public cloud to schedule part of the workflow. In the experimental phase, the algorithm was verified using the Work-flowSim simulation platform. The experimental results show that compared with traditional hybrid cloud workflow scheduling algorithms, this scheduling algorithm can effectively help enterprises reduce the cost of renting public clouds in the process of using hybrid clouds at different deadlines, and get faster execution time.
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