A resource allocation and task scheduling method for an edge cloud combined architecture

Abstract

The invention discloses a resource allocation and task scheduling method for edge cloud combination. The method comprises the steps of firstly recording the relevant information of an edge server adjacent to the edge server in the edge server; when the task arrives at an edge server adjacent to the task, using the server to calculate the estimated calculation time and energy consumption cost for sending the task to each server; selecting the edge server with the lowest energy consumption cost from the servers meeting the calculation time required by the task as the task execution position, ifthe server does not meet the requirement, executing the task locally, and if all the servers are in the full load state, issuing the task to the cloud server for execution under the condition that themaximum delay time is met, and finally, after the task arrives at the processing position, using the edge server to carry out the task execution sequence scheduling and data transmission scheduling on the task according to the deadline of the task, so that the purposes of reducing the energy consumption cost of the whole system and balancing the load of the whole edge server are achieved on the premise of ensuring the task delay requirement.

Description

technical field [0001] The invention belongs to the field of edge computing, and specifically relates to the design and implementation of a method for resource allocation and task scheduling under the structure of combining edge computing and cloud computing. Background technique [0002] With the development of related technologies of the Internet of Things, we are entering the era of the Internet of Everything from the era of the Internet of Things. Billions or even tens of billions of connected nodes. While providing more complex functions, massive data will also be generated in the network, and the processing of massive data will be a prominent issue in the development of the Internet of Things in the future. Traditional cloud computing-based solutions send data processing tasks to the cloud computing center, and use the super computing power of the cloud computing center to centrally solve the computing and storage problems of these data. Although the centralized proc...

AI Technical Summary

Problems solved by technology

However, the network architecture combining edge and cloud also brings new challenges. Unlike the cloud computing architecture, in the network architecture combining edge and cloud, the location of task processing also has a choice. For tasks with different characteristics, it is suitable for processing The location is also different, and the scheduling strategy used in cloud computing in the past will no longer be applicable to the current computing architecture combining edge and cloud

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