Cloud-based Workflow Scheduling Optimization Research For Energy Consumption

With the rapid development of cloud computing, the large-scale cloud computing data center established in the global country wide.The problems of high energy consumption and high pollution which arises out of data center are spreading worldwide. If we let these trends go unchecked, Cloud computing will be suffered by the cost and limited by the law. With the promotion of low carbon economy and green energy, how to reduce energy consumption of cloud computing has attracted the attention of the community. Therefore, how to reduce the resource node energy consumption to meet the standard of green energy while keeping even improving the quality of services is one of the urgent problems to be solved.Cloud workflow is the combination of workflow technology and cloud computing technology. It can be widely used in the field of collaborative inter-organizations, such as scientific computing, which need efficient computing performance and mass storage support. After the research we did, we realize that current studies on workflow execution/scheduling methods are just for executing time or cost and that is not suitable for the energy consumption optimization in workflow system. In addition, the lacks of considering integrated optimization of task allocation and resource selection for resource node energy consumption is also a big issue.According to the characteristics of the cloud computing services and requirements, this paper puts forward the energy consumption optimized cloud workflow system on the basis of present situation, development trend and existing problems on workflow execution/scheduling optimization of related research status at home and abroad.The system is decomposed into several modular pieces, and each one is described in detail. Furthermore, it gives the definition of workflow model, resource model and presents the algorithm for energy consumption in cloud computing workflow system.For the energy consumption of cloud in workflow system, this article has presented oriented HMPC scheduling algorithm for energy optimization, which can ensure the workflow execution time efficiency and improve the workflow execution service node’s high energy consumption. Through the multiple sets of workflow application experiment and comparing relevant classical scheduling algorithm, we use open source tools WorkflowSim simulation experiment to verify the effectiveness of the algorithm and have obtained satisfactory results.