Resource placement strategy optimization for IoT oriented monitoring application

Abstract

Cloud computing and the low power wide area network (LPWAN) network represent the key infrastructures for developing intelligent solutions based on the internet of things (IoT). However, the diversity of use cases and deployment scenarios of IoT in the different domains makes optimizing
IoT-based cloud solutions a major challenge. The cloud solution’s cost increases with the increase in central processing unit (CPU) resources and energy consumption. The optimal use of edge material resources in industrial solutions will reduce the consumption of resources and thus optimize cloud infrastructure costs in terms of resources and energy consumption. The article presents the network and application architecture of an IoT monitoring solution based on cloud services. Then, we study the integration of IoT services based on application placement strategies on the fog cloud compared to the traditional centralized cloud strategy. Simulations evaluate the scenarios with the iFogSim simulator and the analyzed results compare the traditional strategy with the cloud-fog. The results show that cost and energy consumption in the cloud can be significantly reduced by processing the application at the end devices level with respect to the possible limit of CPU processing power for each IoT end device. Latency and network usage respect quality of service constraints in cloud-fog placement for this type of monitoring-oriented IoT application.