Optimizing IoT application deployment with fog - cloud paradigm: A resource-aware approach

Abstract

Fog computing is the architecture that most researchers use to build latency-sensitive Internet of Things (IoT) applications. By placing resource-constrained fog devices near the network’s edge, fog computing design delivers less delay than the cloud computing paradigm. Fog nodes use the available resources to process the incoming data, which lowers the data amount that needs to be transferred to the server of the cloud. A system contains fog devices with various levels of computing power. The best system performance is only possible when the appropriate sensor nodes are connected to the parent fog node. In this study, we introduce a cluster head selection algorithm for effective network resource utilization through application deployment in a fog-cloud environment for internet of things-based applications. With the introduction of fog computing, the processing is animatedly dispersed through the cloud layers and fog, enabling the deployment of an application’s modules closer to the foundation of fog-layer devices. The method is general and may be used with various network topologies and a broad range of standardized IoT applications, regardless of load.