# How to Place Your Apps in the Fog -- State of the Art and Open Challenges

arXiv: https://arxiv.org/abs/1901.05717 · HTML: https://mlsanity.com/paper/1901.05717/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Jan 2019.

## Built on by (most cited first, 2 of 2)

- [Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management](https://mlsanity.com/paper/2402.17216/) (2024)
- [Distributed genetic algorithm for application placement in the compute continuum leveraging infrastructure nodes for optimization](https://mlsanity.com/paper/2406.09478/) (2024)

## Abstract (arXiv)

Fog computing aims at extending the Cloud towards the IoT so to achieve improved QoS and to empower latency-sensitive and bandwidth-hungry applications. The Fog calls for novel models and algorithms to distribute multi-service applications in such a way that data processing occurs wherever it is best-placed, based on both functional and non-functional requirements. This survey reviews the existing methodologies to solve the application placement problem in the Fog, while pursuing three main objectives. First, it offers a comprehensive overview on the currently employed algorithms, on the availability of open-source prototypes, and on the size of test use cases. Second, it classifies the literature based on the application and Fog infrastructure characteristics that are captured by available models, with a focus on the considered constraints and the optimised metrics. Finally, it identifies some open challenges in application placement in the Fog.