Container-Based QoS-Aware Service Placement for IoT/IIoTin Fog Environments with Data Analytics for Smart Applications

This paper presents a framework of deploying Internet of Things (IoT), industrial Internet of Things (IIoT) applications such that QoS is taken into account and resource consumption and latency are optimized. The architecture is built on containers and makes intensive use of data analysis in order to forecast workload trends and to dynamically allocate services to fog nodes. One can make ideal judgments about service placement as function of delay, energy, and pricing. The framework achieves this by the dynamic relocation of services to forestall system failure when fog nodes fail or performance falls. Through the use of real world Internet of Things datasets, we have demonstrated that the strategy outperforms standard placement strategies with respect to response and resource efficiency. Thus the approach has been provided which can benefit a number of intelligent applications, such as, city planning, healthcare, and manufacturing. The research also contributes to the development of fog calculating for Internet of Things using Internet of Things ecosystems, as well as, supporting intelligent and scalable solutions for applications of next generation.