Workflow Scheduling Based on Mobile Cloud Computing Machine Learning

In recent years, cloud workflow task scheduling has always been an important research topic in the business world. Cloud means that tasks submitted by users are allocated to appropriate computing resources for execution, and corresponding fees paid real time according usage of resources. For most ordinary users, they mainly concerned with two service quality indicators completion execution cost. Therefore, how providers design a algorithm optimize cost is very issue. This paper proposes on based mobile machine learning, this conducts using literature methods, experimental analysis other methods. article deeply studied computing, scheduling, related theories, system model was established learning from different algorithms used processing time, costs, resource The situation influence results analyzed many aspects. speeds up about 7% under number reduces 2% compared algorithms. obviously optimized scheduling.