# YAFS: A simulator for IoT scenarios in fog computing

arXiv: https://arxiv.org/abs/1902.01091 · HTML: https://mlsanity.com/paper/1902.01091/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Feb 2019.

## Built on by (most cited first, 8 of 8)

- [Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review](https://mlsanity.com/paper/2205.01081/) (2022)
- [Efficient micro data centres deployment for mobile healthcare monitoring systems in IoT urban scenarios](https://mlsanity.com/paper/2302.10201/) (2023)
- [Lifelong Learning for Fog Load Balancing: A Transfer Learning Approach](https://mlsanity.com/paper/2310.05187/) (2023)
- [Fully Distributed Fog Load Balancing with Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2405.12236/) (2024)
- [Adaptive AI-based Decentralized Resource Management in the Cloud-Edge Continuum](https://mlsanity.com/paper/2501.15802/) (2025)
- [A Data Quarantine Model to Secure Data in Edge Computing](https://mlsanity.com/paper/2111.07672/) (2021)
- [SafeTail: Efficient Tail Latency Optimization in Edge Service Scheduling via Computational Redundancy Management](https://mlsanity.com/paper/2408.17171/) (2024)
- [CRAWO: Custom Resources for Adaptive Workload Orchestration](https://mlsanity.com/paper/2607.20490/) (2026)

## Abstract (arXiv)

We propose a fog computing simulator for analysing the design and deployment of applications through customized and dynamical strategies. We model the relationships among deployed applications, network connections and infrastructure characteristics through complex network theory, enabling the integration of topological measures in dynamic and customizable strategies such as the placement of application modules, workload location, and path routing and scheduling of services. We present a comparative analysis of the efficiency and the convergence of results of our simulator with the most referenced entity, iFogSim. To highlight YAFS functionalities, we model three scenarios that, to the best of our knowledge, cannot be implemented with current fog simulators: dynamic allocation of new application modules, dynamic failures of network nodes and user mobility along the topology.