# The Internet of Things, Fog and Cloud Continuum: Integration and Challenges

arXiv: https://arxiv.org/abs/1809.09972 · HTML: https://mlsanity.com/paper/1809.09972/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Sep 2018.

## Built on by (most cited first, 6 of 6)

- [Management of Resource at the Network Edge for Federated Learning](https://mlsanity.com/paper/2107.03428/) (2021)
- [Adaptive AI-based Decentralized Resource Management in the Cloud-Edge Continuum](https://mlsanity.com/paper/2501.15802/) (2025)
- [Distributed genetic algorithm for application placement in the compute continuum leveraging infrastructure nodes for optimization](https://mlsanity.com/paper/2406.09478/) (2024)
- [Personalized Multi-tier Federated Learning](https://mlsanity.com/paper/2407.14251/) (2024)
- [CO-DEFEND: Continuous Decentralized Federated Learning for Secure DoH-Based Threat Detection](https://mlsanity.com/paper/2504.01882/) (2025)
- [A Comparative Study of CNN Optimization Methods for Edge AI: Exploring the Role of Early Exits](https://mlsanity.com/paper/2604.14789/) (2026)

## Abstract (arXiv)

The Internet of Things needs for computing power and storage are expected to remain on the rise in the next decade. Consequently, the amount of data generated by devices at the edge of the network will also grow. While cloud computing has been an established and effective way of acquiring computation and storage as a service to many applications, it may not be suitable to handle the myriad of data from IoT devices and fulfill largely heterogeneous application requirements. Fog computing has been developed to lie between IoT and the cloud, providing a hierarchy of computing power that can collect, aggregate, and process data from/to IoT devices. Combining fog and cloud may reduce data transfers and communication bottlenecks to the cloud and also contribute to reduced latencies, as fog computing resources exist closer to the edge. This paper examines this IoT-Fog-Cloud ecosystem and provides a literature review from different facets of it: how it can be organized, how management is being addressed, and how applications can benefit from it. Lastly, we present challenging issues yet to be addressed in IoT-Fog-Cloud infrastructures.