Hierarchic scheduling method for service and resources in cloud computation environment

Abstract

The invention discloses a hierarchic scheduling method for service and resources in a cloud computation environment, which comprises the stages of submitting a user request, partitioning task units, defining a computation model, defining a storage model, defining a service analysis process, a service scheduling process and a resource scheduling process, evaluating the scheduling and the like, specially comprises the steps: defining and applying a mathematic model of a service combination file into the cloud environment; firstly analyzing the service combination file so as to determine the service priority; and classifying tasks by utilizing a resource pool, executing service through operation characteristics by using a proper resource allocation method, wherein the scheduling method considers data locality and related service completion rate. Observing from simulation experiments, according to the hierarchic scheduling method, the resource utilization rate can be improved, and a higher service completion rate can be realized compared with the default FIFO (First-In First-Out) scheduling of Hadoop. According to the method provided by the invention, the requirements of users and service providers can be met through high-efficiency scheduling and the reallocation of priority.

Description

technical field [0001] The invention belongs to the technical field of computer network application and system structure, and in particular relates to a service and resource hierarchical scheduling method in a cloud computing environment. Background technique [0002] Cloud computing has changed the traditional way of using infrastructure. Among them, effective resource management and service scheduling can solve the problem of excessive consumption or underutilization of resources and improve user satisfaction. Due to the diversity of user needs and service attributes, it is very important to study scheduling algorithms for different applications and service models in cloud environments, and to perform service composition in cloud environments to achieve customization to user requests. To implement service composition in a cloud computing environment, it is important to service scheduling and resource allocation and to meet QoS requirements on this basis. Service composit...

AI Technical Summary

Problems solved by technology

[0005] Previous research on service scheduling algorithms in the Map / Reduce model includes: FIFO scheduling algorithms will occupy system resources for a long time. After other jobs are submitted, they cannot be processed in time due to the lack of system resources, which affects the interactive capabilities of the system and users. The use experience; the fair share scheduling algorithm and the computing power scheduling algorithm need to be pre-configured, so whether the configuration is appropriate or not determines the performance of the system. Hershey's system performance has a large gap

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