Research on Cloud-edge Joint Task Inference Algorithm in Edge Intelligence

Research on Cloud-edge Joint Task Inference Algorithm in Edge Intelligence

With the advent of the era of Internet of things, edge computing is gradually becoming a new computing paradigm in the field of Internet of things. With the rapid development of artificial intelligence technology, edge intelligence (EI) will be the general trend. Compared with the traditional cloud computing mode, the edge computing mode with scattered and limited resources brings great challenges to the training reasoning, model deployment and resource allocation of artificial intelligence services. In this paper, the multi task reasoning scenario in edge intelligence is analyzed, and a multi task cloud edge joint reasoning optimization algorithm based on DNN model is proposed, which is modeled as the optimization problem of minimum average delay in multi task scenario. The binary genetic algorithm and the double nested optimization algorithm of augmented Lagrange algorithm are used to solve the problem.