Multi-user dynamic scheduling-based resource management for Internet of Things applications

The gigantic growth of internet-connected objects worldwide is affected by the diversity of hardware and software components used to build objects and therefore puts Cloud providers in front of resource repartition between end users. This paper addresses this problem in Fog computing environments by proposing a classification-based approach of Cloud servers and heterogeneous devices in order to facilitate the resource management of Internet of Things (IoT) applications and satisfy the customer. The main goal is to enhance the resource allocation for devices that need to find the best way to meet their demands. To this end, basing on the dynamic scheduling of multi-user requests, servers are allocated in parallel and devices are served in parallel to minimize the wait time of each device and serve the maximum of devices at the same time. Experimental results of a hospital system simulation in iFogSim show the effectiveness of the proposed approach in streamlining the patient information flow and its accessibility for health care providers.