# Resource Management in Fog/Edge Computing: A Survey

arXiv: https://arxiv.org/abs/1810.00305 · HTML: https://mlsanity.com/paper/1810.00305/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Sep 2018.

## Built on by (most cited first, 13 of 13)

- [Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration](https://mlsanity.com/paper/2205.01423/) (2022)
- [PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge Computing](https://mlsanity.com/paper/2112.02292/) (2021)
- [A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks](https://mlsanity.com/paper/2508.18803/) (2025)
- [Management of Resource at the Network Edge for Federated Learning](https://mlsanity.com/paper/2107.03428/) (2021)
- [AI Back-End as a Service for Learning Switching of Mobile Apps between the Fog and the Cloud](https://mlsanity.com/paper/2110.00836/) (2021)
- [WW-FL: Secure and Private Large-Scale Federated Learning](https://mlsanity.com/paper/2302.09904/) (2023)
- [Adaptive AI-based Decentralized Resource Management in the Cloud-Edge Continuum](https://mlsanity.com/paper/2501.15802/) (2025)
- [Self-Evolving Multi-Agent Network for Industrial IoT Predictive Maintenance](https://mlsanity.com/paper/2602.16738/) (2026)
- [ScissionLite: Accelerating Distributed Deep Neural Networks Using Transfer Layer](https://mlsanity.com/paper/2105.02019/) (2021)
- [Introducing Federated Learning into Internet of Things ecosystems -- preliminary considerations](https://mlsanity.com/paper/2207.07700/) (2022)
- [Lightweight Strategy for XOR PUFs as Security Primitives for Resource-constrained IoT device](https://mlsanity.com/paper/2210.01749/) (2022)
- [Distributed genetic algorithm for application placement in the compute continuum leveraging infrastructure nodes for optimization](https://mlsanity.com/paper/2406.09478/) (2024)
- [Designing Short-Stage CDC-XPUFs: Balancing Reliability, Cost, and Security in IoT Devices](https://mlsanity.com/paper/2409.17902/) (2024)

## Abstract (arXiv)

Contrary to using distant and centralized cloud data center resources, employing decentralized resources at the edge of a network for processing data closer to user devices, such as smartphones and tablets, is an upcoming computing paradigm, referred to as fog/edge computing. Fog/edge resources are typically resource-constrained, heterogeneous, and dynamic compared to the cloud, thereby making resource management an important challenge that needs to be addressed. This article reviews publications as early as 1991, with 85% of the publications between 2013-2018, to identify and classify the architectures, infrastructure, and underlying algorithms for managing resources in fog/edge computing.