Cloud Computing Energy Optimization Method and System Based on Phase Space

Abstract

The invention relates to the field of cloud computing, and discloses a cloud computing energy consumption optimization method and system based on phase space, so as to optimize energy consumption in cloud computing, reduce task allocation time, and improve task allocation efficiency; the method of the invention includes obtaining cloud Calculate all nodes in the system and their context information, and establish an energy consumption model; measure the total energy consumption of all tasks being executed by the node, and establish a static energy consumption phase space based on the total energy consumption; use the energy consumption model to predict new The energy consumption required by the task, and establish the dynamic energy consumption phase space; calculate the optimal sub-phase space according to the static energy consumption phase space; predict the energy consumption of each node in the optimal sub-phase space for the new task, and calculate the Phase space and dynamic energy consumption Phase space design task scheduling algorithm, and determine the optimal task allocation scheme for new tasks.

Description

technical field [0001] The invention relates to the field of cloud computing, in particular to a cloud computing energy optimization method and system based on phase space. Background technique [0002] The emergence of cloud computing enables enterprises to obtain a large amount of computing and storage resources online, and only needs to pay according to the length of use of resources, avoiding investment in expensive IT infrastructure. With the rapid development of cloud computing technology, the number of global cloud computing data centers is increasing, and the annual energy consumed by data centers accounts for an increasing proportion of the world's energy consumption. While the cloud computing data center consumes a large amount of energy every year, it also puts a certain pressure on the environment (such as the greenhouse gas generated by the data center). The energy consumption of cloud computing has gradually become the focus of researchers. The cloud computing...

AI Technical Summary

Problems solved by technology

However, the above energy consumption model is more concerned with the energy consumption status of a single server node, and the energy consumption estimation of the high-performance computing center is simply to accumulate the energy consumption of the server nodes

Therefore, the above method is more suitable for the situation where the energy consumption state coupling between servers is not obvious, and is not suitable for highly coupled cloud computing systems

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