English

GAP: Game Theory-Based Approach for Reliability and Power Management in Emerging Fog Computing

Distributed, Parallel, and Cluster Computing 2024-12-17 v1 Emerging Technologies Computer Science and Game Theory

Abstract

Fog computing brings about a transformative shift in data management, presenting unprecedented opportunities for enhanced performance and reduced latency. However, one of the key aspects of fog computing revolves around ensuring efficient power and reliability management. To address this challenge, we have introduced a novel model that proposes a non-cooperative game theory-based strategy to strike a balance between power consumption and reliability in decision-making processes. Our proposed model capitalizes on the Cold Primary/Backup strategy (CPB) to guarantee reliability target by re-executing tasks to different nodes when a fault occurs, while also leveraging Dynamic Voltage and Frequency Scaling (DVFS) to reduce power consumption during task execution and maximizing overall efficiency. Non-cooperative game theory plays a pivotal role in our model, as it facilitates the development of strategies and solutions that uphold reliability while reducing power consumption. By treating the trade-off between power and reliability as a non-cooperative game, our proposed method yields significant energy savings, with up to a 35% reduction in energy consumption, 41% decrease in wait time, and 31% shorter completion time compared to state-of-the-art approaches. Our findings underscore the value of game theory in optimizing power and reliability within fog computing environments, demonstrating its potential for driving substantial improvements

Keywords

Cite

@article{arxiv.2412.11310,
  title  = {GAP: Game Theory-Based Approach for Reliability and Power Management in Emerging Fog Computing},
  author = {Abolfazl Younesi and Mohsen Ansari and Alireza Ejlali and Mohammad Amin Fazli and Muhammad Shafique and Jörg Henkel},
  journal= {arXiv preprint arXiv:2412.11310},
  year   = {2024}
}

Comments

13 pages, 10 figures

R2 v1 2026-06-28T20:36:01.215Z