Dynamic migration method of video tasks in edge computing environment

Abstract

The invention discloses a dynamic migration method of video tasks in an edge computing environment. Multiple ECNs (Edge Compute Nodes) are selected in an ECN cluster under the edge environment to runa task scheduling migration scheduler to be responsible for distribution and scheduling work of the tasks, and the other ECNs in the cluster undertake task migration work and provide computing resources. The computing task migration scheduler executes task migration decision in each scheduling cycle to determine whether the tasks are executed locally in the ECNs or migrated to a data center, and tasks needing to be migrated to the data center are directly sent to a task execution unit of the remote-end data center through an ECN transmission unit for analysis processing. According to the method, the tasks are dynamically scheduled and processed on the basis of meeting network bandwidth and calculation costs, goals of reducing transmission time delay of edge data and improving task analysisprocessing speed are achieved, thus low delay time and high response of a task migration process are effectively guaranteed, and video service experience of users is improved while higher video service quality is realized.

Description

technical field [0001] The invention relates to a video task dynamic migration method in an edge computing environment, and belongs to the field of combining edge computing technology and video technology application. Background technique [0002] With the rapid development of network technology, we have entered the era of the Internet of Everything, and the number of network edge devices is increasing rapidly. According to the estimate of Cisco Global CloudIndex, by 2019, up to 45% of network data will be analyzed and processed at the edge of the network. And the resulting edge data is as high as Zettabyte level. The calculation and storage of the traditional cloud computing model are performed in a centralized manner in the data center. Under the background of the Internet of Everything, the centralized cloud computing model has the following problems to be solved when processing video services: 1) The linear growth of computing equipment in the data center cannot Efficie...

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Problems solved by technology

[0005] In order to reduce the impact of task transmission delay and energy consumption, Liyao Xiang et al. proposed a cluster migration strategy and designed an algorithm to migrate multiple tasks to the data center in a relatively energy-saving manner. energy consumption, but cannot meet the needs of low-latency and high-response video processing tasks during migration; You Lu et al. proposed a guiding forwarding scheme for content retrieval in edge computing environments, sharing hot video content to adjacent locations Other edge nodes can effectively reduce the communication overhead caused by duplicating the query copy. Due to the long distance between the edge node and the data center, the communication overhead and data processing overhead of transmitting hot video content for the first time are still high; Byung-Gon Chun et al. proposed A method of task cloning and migration. Through static analysis and dynamic analysis, tasks are split into multiple parts, and tasks are uniformly scheduled according to factors such as delay, energy consumption, and resource requirements. Although this method reduces communication overhead through task migration , however incurs additional local computational overhead when analyzing video tasks

[0006] By comparing the progress and results of the above-mentioned task migration problem, it can be found that this kind of method is not ideal for the delay optimization effect of video services in the edge computing environment. The data center is close to the data source. In the edge computing environment, the impact of a long distance on the migration delay of video tasks cannot be ignored.

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