In terms of iFog VANET Spine-leaf Congestion Control, three distinct algorithms are studied, namely the proposed Linear Routing Algorithm (LRA), LEACH, and Collection tree protocol (CTP). For latency profile, the results indicate that Fog and cloud streams had 20.31% and 77.69%, respectively. For traffic workload utilization, the results show that 83.33% of the traffic workload is utilized at the Fog layer while 16.67% is consumed in the Cloud layer. iFog Spine-leaf architecture for Fog-Computing and Cloud-Computing are compared using two key metrics. In the validation study, a secure Docker-based iFog CPS experiment is carried out using traffic trace files from C++ Modeller. Use-case application of Artificial Intelligence (AI) in Vehicular ad-hoc Networks (VANETs) is introduced for data stream pro-visioning. Individual edge clusters are connected to the Edge-Fog layer, which communicates with iFog gateways for processing streams' requests.

This paper presents a dynamic Cyber-physical architecture that leverages iFog layers to map location-based services (LBS) on a Spine-leaf datacenter Clos topology.

Intelligent Fog Cyber-Physical Social Systems (iFog CPSS) is a novel Smart City project that uses intrinsic processes to automate microservices such as edge-to-Fog or Fog-to-Cloud monitoring of complex real-time activities. The results reveal that the message queue-based approach successfully relieves the latency cost of reliable data transmission in the inner fog. We then present the performance results of extensive simulation scenarios for up to 100 clients communicating with 256 sensors simultaneously over the proposed platform. We provide a comprehensive analysis of timing constraints and delay characteristics of both methods. We compare the proposed messaging model with a conventional subscribe-update-notify based data flow approach for the orchestration of reliable data transfer. In this study, we address the data transfer challenges in a scalable fog architecture and propose a message queue based fast reliable data transmission mechanism. However, it is essential to achieve effective resource provisioning and reliable data transfer inside the fog to utilize these advantages. Fog solutions promise numerous advantages to real-time IoT services in a heterogeneous network. Fog computing-based IoT paradigm is gaining more importance as it solves high latency challenges of cloud computing-based IoT.

Iot monitor cpu usage