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A method for optimizing energy consumption of mobile platforms based on Markov decision process

An optimization method and technology of mobile platform, applied in the direction of reducing energy consumption, climate sustainability, sustainable communication technology, etc., can solve the problem of high energy consumption

Active Publication Date: 2021-02-05
NORTHWEST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In real life, users have different mobile phone download power and download time under different environmental conditions, and the energy consumption required to refresh pictures on Weibo is relatively high.

Method used

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  • A method for optimizing energy consumption of mobile platforms based on Markov decision process
  • A method for optimizing energy consumption of mobile platforms based on Markov decision process
  • A method for optimizing energy consumption of mobile platforms based on Markov decision process

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Embodiment Construction

[0021] The technical solution of the present invention will be described in detail below in conjunction with the embodiments and the accompanying drawings, but is not limited thereto.

[0022] like figure 1 As shown, the user logs in to the Mix test app, the app automatically jumps to the Sina Weibo user authentication interface, and enters the account password to obtain the user's Token password. The Token password is valid within a certain period of time, and the next login does not need to be re-authenticated.

[0023] After the user logs into the Mix test APP, the application will automatically collect the user's environment status value. The environment status value includes the network signal (mainly 4G and Wi-Fi network) strength level value, time interval value, mobile phone remaining power value, and the user refreshes Weibo Frequency value, sort the collected environmental status values ​​in the format set by the database, store them in the local database of the mobi...

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Abstract

A method for optimizing energy consumption of mobile platforms based on Markov decision process. This method considers the network status of different environments, and selects the optimal strategy in the decision table generated by the Markov decision process according to the current power of the mobile phone and the user's refresh frequency. Dynamically select the best network access and refresh and download the best picture format. This method not only reduces the refreshing time, but also can reduce the energy consumption of the mobile platform. Experimental results show that compared with the image refresh mode using a single network, the energy consumption optimization method proposed by the present invention reduces energy consumption by about 12.1% on the premise of not reducing the number of user refreshes.

Description

technical field [0001] The invention belongs to the technical field of computer network communication, and in particular relates to a method for optimizing energy consumption of a mobile platform based on a Markov decision process. Background technique [0002] With the continuous innovation of technology, the market share of smart mobile devices continues to increase. At the same time, with the development and improvement of wireless access network technology, the mobile Internet has become the fifth development cycle after mainframes, minicomputers, personal computers, and desktop Internet. As of June 2016, the number of mobile Internet users in China has reached 656 million. Among Internet users, the number of Internet users using mobile phones has increased from 90.1% at the end of 2015 to 92.5%. Internet users only use mobile phones to account for 24.5%. Concentrate on mobile terminals. [0003] As a form of network service centered on human social interaction, social...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W36/00H04W36/14H04W52/02H04L12/58
CPCH04W36/0094H04W36/14H04W52/0212H04L51/52Y02D30/70
Inventor 高岭郭延超王海杨旭东郑杰
Owner NORTHWEST UNIV
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