A workflow unloading optimization algorithm in a mobile edge environment

Abstract

The invention discloses a workflow unloading optimization algorithm in a mobile edge environment, comprising the following steps: step S1, constructing a workflow scheduling model under the mobile edge environment; step S2, accord to that topology structure, searching a critical path base on the local calculation amount of the workflow, respectively storing nodes and remaining node on the criticalpath into a key node queue and a remaining node queue and waiting for scheduling; step S3, after that eNB node is abstracted into a topology structure, accord to a user history moving path and combining with a prediction model, obtaining a qualified eNB set, and accord to the prediction probability, selecting an optimal unloadable eNB according to the prediction speed and the prediction direction, and providing the eNB to a user for performing task unloading; step S4, dynamically dividing that tasks accord to the scheduling strategy into local execution or unloading to the edge side for execution, and dynamically updating the critical path during the scheduling process; step S5, according to the scheduling result, assigning tasks to the devices under the mobile edge environment until thescheduling of the entire workflow is completed.

Description

technical field [0001] The invention relates to the technical field of mobile edge computing environment, in particular to a workflow unloading optimization algorithm in a mobile edge environment. Background technique [0002] With the continuous development of smart phones and the continuous emergence of technologies such as face recognition, natural language processing, and VR, users' demands for portable management of mobile devices and processing a large amount of timely information are also gradually increasing. In this case, how to ensure that the mobile device can still maintain high performance under the condition of limited computing power and battery capacity is a technical problem to be solved in this field. When dealing with changes in the network environment in the edge environment, based on The response strategy of static scheduling has poor real-time performance, and the strategy based on edge side selection has the problem of high unloading failure rate, whic...

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Problems solved by technology

2. In the mobile edge computing environment, the real network environment is a necessary consideration in the study of mobile edge computing scheduling. Unreasonable task offloading will cause a lot of time and energy consumption for the device, so real-time scheduling of tasks is required.

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