Cost‐aware cloud bursting in a fog‐cloud environment with real‐time workflow applications

Abstract

SummaryCloud bursting is a concept originating from the hybrid cloud computing paradigm. During workload spikes, the local resources of the private cloud are supplemented by resources in the public cloud. This technique could also be applied in a fog computing environment, in order to handle workload fluctuations, by offloading applications to the cloud. Toward this direction, in this article, we propose a strategy for the utilization of supplementary cloud resources, in order to assist in the processing of Internet of Things workflow jobs that arrive dynamically in a fog environment. As the cloud involves higher data transfer latency and monetary cost, our approach takes into account these two factors, in addition to the real‐time constraints of the workload. The proposed scheduling heuristic is based on the tradeoff between performance and monetary cost. During resource selection, different contribution factors of these two parameters are assessed. Furthermore, the proposed scheduling method is compared against a baseline policy that utilizes only the fog resources. The simulation experiments were carried out under different sizes of workflow input data and for workloads with soft and hard deadlines.