Resource allocation method for embedded edge computing platform

Abstract

The invention discloses a resource allocation method for an embedded edge computing platform, and aims to provide a simple, reliable and quickly deployable distributed computing resource allocation method for the embedded edge computing platform. According to the technical scheme, the method comprises the steps that a Json file serves as a carrier, the Json file is arranged according to a data propagation path and node calculation operation in a calculation graph, and calculation operation programs needing to be additionally supplemented are packaged into a compressed file together; then, a calculation task (namely, a Json file package) is injected into the embedded edge calculation platform, a Json file is automatically analyzed, a calculation graph is recovered, the requirements of calculation and communication resources are decomposed according to the calculation graph, and a mapping graph is formed; and finally, the mapping graph is used to complete the deployment from the calculation demand to the hardware resources; and if the mapping is not successful, the decomposition mode of the calculation graph is adjusted according to the reason of failure feedback to form a new mapping graph, and then mapping is performed again.

Description

technical field [0001] The invention relates to a distributed computing resource configuration method for an embedded edge computing platform. Background technique [0002] In recent years, as the capabilities of sensors and end devices have become stronger, the demand for data volume and data processing diversification has exploded. Especially with the continuous emergence of new applications such as the Internet of Things, autonomous driving, and virtual reality, traditional cloud-based big data processing and artificial intelligence computing can no longer solve existing problems well, so a new computing model has emerged, called edge computing. Edge computing is at the edge of the network, that is, close to the source of data generation, using network edge nodes to process and analyze data and provide near-end computing services. [0003] Edge computing is becoming increasingly important as part of the Industrial Internet of Things. Due to the limited resources of IoT...

AI Technical Summary

Problems solved by technology

However, for the above core issues, there is no implementation standard yet

And compared with the cloud computing center, the computing, communication, storage, power supply and other resources of the edge computing platform are relatively limited, and it is not suitable for deploying heavyweight system services. Therefore, a lightweight resource allocation method suitable for the edge computing platform is urgently needed

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