A workflow optimization method in mobile cloud environment

Abstract

The invention discloses a workflow optimization method in a mobile cloud environment, comprising the following steps: Step S1: preprocessing the workflow submitted by the user; Step S2: constructing a workflow model in the mobile cloud environment; Step S3: based on The improved genetic algorithm generates the optimal scheduling scheme of the workflow; Step S4: Assign tasks to the devices in the mobile cloud according to the scheduling results. Compared with the existing technology, the present invention configures the optimal voltage frequency of the equipment by adjusting the voltage frequency, and uses the obtained voltage frequency as a code to conduct an optimization search with a genetic algorithm to seek the reliability and energy consumption of the equipment in the mobile cloud environment. Optimal task scheduling can achieve the purpose of multi-objective optimization by searching at a faster speed, especially suitable for terminal equipment users to process large amounts of data and massive data calculations.

Description

technical field [0001] The invention relates to the field of mobile cloud computing environment, in particular to a workflow optimization method in the mobile cloud environment. Background technique [0002] Mobile cloud computing is the product of the integration of factors such as the popularization of mobile devices, the improvement of mobile device performance, the improvement of mobile network stability, and the development of anytime, anywhere business model. It aims to use the cloud platform to distribute the tasks in the workflow to the end users in a reasonable and constrained manner, thereby reducing the energy consumption and computing burden of the user terminal, and making it easy for users to manage and process a large number of workflows anytime, anywhere using only mobile devices. timeliness of information. [0003] Compared with traditional servers and desktop devices, mobile devices still have limitations in power consumption, storage space, and computing ...

AI Technical Summary

Problems solved by technology

[0003] Compared with traditional servers and desktop devices, mobile devices still have limitations in power consumption, storage space, and computing power. How to integrate information resources, process massive data, and reduce device energy consumption is placed in the mobile cloud environment. Unavoidable Problems in Stream Scheduling Technology

Among the existing solutions to this problem, the method of providing platform services is adopted, and the characteristics of resource sharing and high computing power of the cloud server are used to process a large amount of information, which is different from the workflow processing scheduling mode of the cloud environment. The task processing time, equipment reliability and energy consumption in the flow are the key points and difficulties in dealing with the workflow scheduling in this environment

On the issue of workflow scheduling in the mobile cloud environment, a lot of research work has been done at home and abroad, but most of the current workflow scheduling algorithms in the mobile cloud computing environment only consider one-sided factors, and do not comprehensively consider Minimize energy consumption and maximize reliability of equipment under preset workflow deadline constraints

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