Fog Computing and IoT Integration for Latency Reduction: A Case Study

The Internet of Things (IoT) has risen rapidly and created a need for computing architectures with the ability to aid real-time applications with the least latency. Conventional cloud-only setups often experience high latency due to physical distance and network congestion, thus, unsuitable for time-sensitive applications. Four of the architectural models currently proposed in the literature are assessed in the present paper: Cloud-only, Edge-only, Fog Multi-layer, and Smart Hybrid; each of them is evaluated in a large-scale simulation aimed at simulating a smart city environment with 1,000 various IoT devices, such as sensors, cameras, and wearables generating dynamic traffic. The outcomes indicate that Edge-only architecture recorded the least mean latency of 0.2417 seconds compared to Smart Hybrid with 0.3156 seconds and Fog Multi-layer with 0.3874 seconds mean latencies whereas the Cloud-only model presented the highest latency with 0.5231 seconds. Given that there existed significant differences between the architectures (p < 0.0001) based on the results of the statistical analysis carried using the one-way ANOVA. Such results explain the promise of adaptive and context-sensitive hybrid systems and allow reducing latency in any IoT deployment in the future and designing an IoT-oriented system that supports latency-sensitive applications in smart cities in a more scalable manner.