Access Algorithms and Scheduling Mechanisms for Large-Scale AI Data Streams
In the edge access cluster of artificial intelligence data flow,it is important to have higher access bandwidth,but the efficient AI data flow access algorithm and scheduling mechanism can better give full play to the hardware performance such as access server network card.This paper proposes a concurrent access algorithm and scheduling mechanism for large-scale AI data flow.Aiming at the unstable access of AI data unit with dynamic change in size,a area dynamic group access algorithm and a data flow migration and scheduling mechanism based on access server resource prediction are designed.The cluster experiment results show that the area dynamic group access algorithm can better satisfy the access request of large-scale AI data stream.On the prem-ise of ensuring the total concurrency of data flow in the access server cluster,the flow scheduling mechanism based on resource pre-diction makes the utilization of access server resources balanced and greatly reduces the packet loss rate of system AI data unit.
AI data flowUDParea dynamic group accessdata flow migration scheduling
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