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

翻译：雾计算带来了数据管理的变革性转变，为提升性能和降低延迟提供了前所未有的机遇。然而，雾计算的关键方面之一在于确保高效的功率与可靠性管理。为应对这一挑战，我们提出了一种新颖模型，该模型采用基于非合作博弈论的策略，在决策过程中实现功耗与可靠性之间的平衡。我们提出的模型利用冷主/备份策略（CPB），通过在故障发生时将任务重新执行至不同节点来保证可靠性目标，同时借助动态电压频率调节（DVFS）降低任务执行期间的功耗，从而最大化整体效率。非合作博弈论在我们的模型中起着关键作用，它有助于制定在降低功耗的同时保持可靠性的策略与解决方案。通过将功耗与可靠性之间的权衡视为非合作博弈，我们提出的方法实现了显著的节能效果：与现有先进方法相比，能耗降低高达35%，等待时间减少41%，完成时间缩短31%。我们的研究结果凸显了博弈论在优化雾计算环境中功率与可靠性方面的价值，证明了其在推动实质性改进方面的潜力。