# Towards Self-Adaptive Peer-to-Peer Monitoring for Fog Environments

arXiv: https://arxiv.org/abs/2205.04142 · HTML: https://mlsanity.com/paper/2205.04142/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 May 2022.

## Built on by (most cited first, 1 of 1)

- [An Energy-Aware Approach to Design Self-Adaptive AI-based Applications on the Edge](https://mlsanity.com/paper/2309.00022/) (2023)

## Abstract (arXiv)

Monitoring is a critical component in fog environments: it promptly provides insights about the behavior of systems, reveals Service Level Agreements (SLAs) violations, enables the autonomous orchestration of services and platforms, calls for the intervention of operators, and triggers self-healing actions. In such environments, monitoring solutions have to cope with the heterogeneity of the devices and platforms present in the Fog, the limited resources available at the edge of the network, and the high dynamism of the whole Cloud-to-Thing continuum. This paper addresses the challenge of accurately and efficiently monitoring the Fog with a self-adaptive peer-to-peer (P2P) monitoring solution that can opportunistically adjust its behavior according to the collected data exploiting a lightweight rule-based expert system. Empirical results show that adaptation can improve monitoring accuracy, while reducing network and power consumption at the cost of higher memory consumption.