Goal-driven scheduling model in edge computing for smart city applications

A formidable challenge in scheduling user applications lies in collecting and representing the user's goals and requirements. We introduce a “science goal” as a mechanism for users to define scientific objectives and conditions of interest. To provide an abstraction to run applications on an ensemble of edge computing nodes, we implement a two-layered scheduler—cloud and edge scheduler. In this scheduling model, the users submit their goals to the cloud scheduler. These goals are conveyed to the appropriate nodes based on a variety of constraints including geographical area, resource availability, node capabilities, and applicability. The edge scheduler, with complete understanding of the current conditions, assumes the responsibility for executing the applications on the nodes so that the users' science goals are met. This paper provides a framework for the two-layered scheduling model for goal-driven edge computing and motivates and informs its architecture through a case study.