A Processing Delay Tolerant Workflow Management in Cloud-Fog Computing Environment (DTWM_CfS)

During the past few years, powerful Fog computing has become a perfect counterpart to the cloud computing where the resources are dealing comfortably with computational, communicational and data needs of recently advanced cloud based Internet of Things (IoT) applications. Studying the interoperability and collaboration among the Fog (Edge) and Cloud (Core) for collective service provisioning has recently gained a considerable attention of researchers. Where, a delay tolerant management of IoT workflows and distributing their tasks among the fog and cloud node was became an important issue. As a possible defeat for this, a successive association among native fog nodes and the hired cloud nodes were exploited. In this work, a heuristic-based delay tolerant task scheduling and workflow management system for Cloud-fog computing (DTWM_CfS) were formulated and proposed for distributing the workflow tasks of IoT applications to the most successive fog or cloud resource nodes for execution. The proposed DTWM_CfS ensures efficient utilization of underlying resources by diminishing the average makespan time and total cost up to 11.23% and 10.6% respectively when compared with other existing methods. Simulation results of DTWM_CfS also ensure a better Cost Makespan Trade-off gain up to 42.6 % when compared with other existing methods.