The application belongs to the technical field of network services, and discloses a high-availability
big data stream processing request
placement method in a serverless edge network. The purpose is to meet the reliability requirements of users while minimizing
processing delay. An
effective algorithm is designed to find a suitable number of instances for the function of each
data stream processing request, and to place the request while minimizing the average
delay experienced by each user while meeting its reliability requirements. After the request is placed, the input
data rate may change and is uncertain. An
online learning algorithm is designed to predict the method to predict the
data rate and dynamically adjust the standby instances to absorb the
uncertain data rate. Based on the experiment of a real
data set, it is shown that the placement problem of
big data stream processing in the edge serverless network is effectively solved.