Container-technology-based video monitoring cloud service platform realization method and system

Abstract

The embodiment of the invention discloses a container-technology-based video monitoring cloud service platform realization method and system. The method comprises: an IVM receives a video service task issued by a user by a VS and a correlated parameter of the task; the IVM generates a resource demand according to the video service task and applies for resources to a resource management device according to the resource demand; the resource management device selects one calculation node server, satisfying the resource demand, among calculation node server as a host machine of the video service task and sends the resource demand and the correlated parameter to the host machine; and the host machine distributes resources to the video service task and establishes a C-IVU based on a video service image and the C-IVU operates the video service and executes the video service task according to the correlated parameter of the video service task. According to the invention, compared with the traditional virtual-machine-based video monitoring cloud realization method, the provided method enables the calculation performance loss to be reduced and the resource utilization rate to be improved.

Description

technical field [0001] The present invention relates to the technical field of intelligent video surveillance, in particular to a platform implementation method and system for a video surveillance cloud service based on container technology. Background technique [0002] In recent years, due to the increasing demand for smart cities and public safety, the use of artificial video surveillance methods has been far from meeting the needs. Therefore, intelligent video surveillance technology emerged and quickly became a research hotspot. Development of stand-alone hardware After Moore's Theorem is broken, stand-alone servers can no longer bear the increasingly heavy resource burden, and cannot cope with the demand for massive video services of today's intelligent video surveillance systems. With the continuous development of distributed computing and other related technologies, cloud computing emerges as the times require, which promotes the development of the video surveillance...

AI Technical Summary

Problems solved by technology

[0011] In the above implementation method, since the hardware resources of the virtual machine are virtualized through the Hypervisor, it needs to be transformed into the use of actual physical resources through a multi-level intermediate layer, which causes a large loss of computing performance; one physical machine can virtualize several virtual machines, However, the virtual machine itself requires additional resource overhead, resulting in waste of resources, and the management granularity of the virtual machine is too large, that is, the resource granularity required for virtual machine allocation is large, such as a CPU with at least 1 core, and a memory with at least 512mb. Therefore, it is easy to cause excessive resources. Fragmentation, which reduces resource utilization

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