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Calculation method of minimum energy consumption in green cloud service providing

A computing method, cloud service technology, applied in the field of mobile micro-learning, which can solve problems such as limited size and weight

Active Publication Date: 2017-11-03
HENAN UNIV OF SCI & TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

The provision and completion of mobile micro-learning requires continuous support between energy, storage and computing resources, but the mobility of mobile terminals largely limits its size and weight, resulting in its processing power, memory capacity, network connection and The problem of battery capacity and other aspects is becoming more and more prominent

Method used

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  • Calculation method of minimum energy consumption in green cloud service providing
  • Calculation method of minimum energy consumption in green cloud service providing
  • Calculation method of minimum energy consumption in green cloud service providing

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Embodiment Construction

[0064] Such as Figure 1~4 As shown, a minimum energy consumption calculation method in green cloud service provision, its technical solution is: including the following steps:

[0065] A. The process of building the keyword thesaurus L:

[0066] A101. Collect historical resources in mobile micro-learning to form a sample set;

[0067] A102. The sample set in the A101 step is divided into a training set and a test set, wherein the training set is The test set is Among U and V, u 1 , u 2 ,...,u φ and v 1 , v 2 ,...,v φ is a large sample class with a large number of bytes, and It is a small sample class with a small number of bytes;

[0068] A103. Utilize the category averaging method to reorganize the small sample class in the training set U in the A102 step to form a relatively uniform new training set U'={u 1 , u 2 ,...,u φ , u′ φ+1 , u′ φ+2}, where u′ φ+1 ={u φ+1 , u φ+2},

[0069] What needs to be clarified is that the category equalization method ...

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Abstract

The invention provides a calculation method of minimum energy consumption in green cloud service providing, and aims to overcome the resource bottleneck problem of a mobile terminal. The method comprises the following steps: A, a process of constructing a keyword word library L; B, a word frequency classification process; C, resource deployment for a new user request sent by a mobile user due to mobile micro-learning; and D, minimum energy function construction for the new user request. According to the method, dynamic TF-IDF is adopted for text classification, resources with high correct rates are placed on local cloud, resources with low correct rates are placed on public cloud, a two-layer cloud architecture model is constructed, and deployment of the mobile micro-learning resources is completed; on the basis of network environment and device state characteristics of real-time changing, a grey wolf optimizer (GWO) is utilized to estimate the energy consumption per byte processed by a system in a current environment state; and finally, a green and high-efficient total energy consumption function is constructed through analyzing a relationship between the user request and two-layer cloud architecture service providing.

Description

technical field [0001] The invention relates to the field of mobile micro-learning, in particular to a method for calculating minimum energy consumption in green cloud service provision. Background technique [0002] Green cloud service refers to the comprehensive consideration of energy and performance factors in the process of service provision, and seeks the solution with the least energy consumption cost under the premise of satisfying user performance. Based on the collaborative service provision process of local cloud and public cloud, this paper studies the problem of minimum energy consumption in the process of service provision. [0003] Mobile micro-learning is a new type of learning model produced with the continuous development and integration of cloud computing and mobile Internet. Or (information) service, and present the learning mode of learning content with the help of mobile terminal equipment. The core goal of mobile micro-learning is to ensure that lear...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06F17/30
CPCG06F9/5088G06F16/35Y02D10/00
Inventor 郑瑞娟张明川吴庆涛朱军龙张茉莉白秀玲魏汪洋杨丽
Owner HENAN UNIV OF SCI & TECH
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