Cloud computing data center based unified resource scheduling energy-saving method

Abstract

The invention discloses a cloud computing data center based unified resource scheduling energy-saving method. The method comprises the following steps: 1, initializing a network node and a virtual machine queue; 2, storing a virtual machine request in the virtual machine queue; 3, arranging virtual machines in a descending order according to a resource request number of the virtual machines; 4, traversing all network nodes in sequence, and judging whether a network node meets a request requirement of a current virtual machine or not; if yes, taking a network node with lowest energy consumption, requested by the current virtual machine, as a target placement node, and otherwise, looking for a network node with most residual available resources, emigrating one virtual machine on the node, and placing the current virtual machine; 5, sequentially selecting a next virtual machine as a current virtual machine, and making a judgment again; and 6, optimizing system energy consumption again. The method has the advantages that a contradictory relation between a power consumption minimization problem and SLA requirement satisfaction is balanced; the method is an energy consumption optimization oriented resource scheduling algorithm; and the method has higher efficiency in energy consumption optimization.

Description

technical field [0001] The invention belongs to the field of cloud computing, and specifically relates to an energy-saving method for unified resource scheduling based on a cloud computing data center. Background technique [0002] With the introduction and development of cloud computing, the problem of high energy consumption in data centers has attracted widespread attention from all walks of life. A large number of computing resources and storage resources have been transferred from distributed and loosely placed to centralized in the cloud, which has brought great benefits to the efficient management of energy consumption. Greater challenge. Due to the increasing amount of data in cloud computing data centers, designers and managers of cloud computing infrastructure (IaaS) are facing huge financial incentives and regulatory pressures, hoping to find effective strategies to reduce the operation and maintenance of cloud computing systems. Cost, reduce energy consumption o...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the problems of high complexity and inconspicuous energy-saving effect in the energy management of data center resource scheduling in the prior art, the present invention proposes a unified resource scheduling energy-saving method based on cloud computing data center

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