Service placement strategy for joint network selection and resource scheduling in edge computing

In the edge computing, service placement refers to the process of installing service platforms, databases, and configuration files corresponding to computing tasks on edge service nodes. In order to meet the latency requirements of new types of applications, service placement in edge computing becomes critical. The service placement strategy must be carried out in accordance with the relevant tasks within the program. However, previous research has paid little attention to related tasks within the application. If the service placement strategy does not consider task relevance, the system will frequently switch services and cause serious system overhead. In this paper, we mainly study the problem of service placement in edge computing. At the same time, we considered the issue of network access point selection during data transmission and the dependencies of task execution. We propose a Dynamic Service Placement List Scheduling (DSPLS) algorithm based on dynamic remaining task service time prediction. We conducted relevant simulation experiments, and our algorithm took the least amount of time to complete the task.