Swarm Intelligence-Based Algorithm for Workload Placement in Edge-Fog-Cloud Continuum

Kefan Wu, Abdorasoul Ghasemi, Melanie Schranz

2025

Abstract

This paper addresses the workload placement problem in the edge-fog-cloud continuum. We model the edge-fog-cloud computing continuum as a multi-agent framework consisting of networked resource supply and demand agents. Inspired by the swarm intelligence behavior of the ant colony optimization, we propose a workload scheduler for the arriving demand agents to increase local resource utilization and reduce communication costs without relying on a centralized scheduler. Like the ants, the demand agents will release pheromones on the resource agent to indicate the available resources. The next arriving demand agent will most probably choose a neighbor, following the pheromone value and communication cost. The framework’s performance is evaluated in terms of local resource utilization, dependency on fog and cloud, and communication cost. We compare these metrics for the ant-inspired algorithm with random and greedy algorithms. The simulation results reveal that the proposed algorithm inspired by swarm intelligence can increase resource utilization at the edge and reduce the dependency on higher layers, while also decreasing the communication cost for the task of resource allocation.

Paper Citation

in Harvard Style

Wu K., Ghasemi A. and Schranz M. (2025). Swarm Intelligence-Based Algorithm for Workload Placement in Edge-Fog-Cloud Continuum. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 310-317. DOI: 10.5220/0013140800003890

in Bibtex Style

@conference{icaart25,
author={Kefan Wu and Abdorasoul Ghasemi and Melanie Schranz},
title={Swarm Intelligence-Based Algorithm for Workload Placement in Edge-Fog-Cloud Continuum},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2025},
pages={310-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013140800003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Swarm Intelligence-Based Algorithm for Workload Placement in Edge-Fog-Cloud Continuum
SN - 978-989-758-737-5
AU - Wu K.
AU - Ghasemi A.
AU - Schranz M.
PY - 2025
SP - 310
EP - 317
DO - 10.5220/0013140800003890
PB - SciTePress