A Dynamic Migration Method of Video Tasks in Edge Computing Environment

Abstract

The invention discloses a method for dynamically migrating video tasks in an edge computing environment. In an ECN cluster in an edge environment, several ECNs are selected to run computing task scheduling migration schedulers, which are responsible for task distribution and scheduling, and other ECNs in the cluster undertake Tasks migrate jobs and provide computing resources. The computing task migration scheduler executes the task migration decision in each scheduling cycle, and decides whether the task is executed locally in the ECN or migrated to the data center. The tasks that need to be migrated to the data center are directly sent to the remote data center through the ECN transmission unit. The task execution unit performs analysis and processing. On the basis of satisfying network bandwidth and computing cost, the present invention dynamically schedules and processes tasks, realizes the goal of reducing the transmission delay of edge data and improving the task analysis and processing speed, thereby effectively ensuring low delay and high task migration process. Response, to improve the user's video service experience while achieving high video service quality.

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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