The management of fog computing applications is a challenging task that requires dealing with a dynamic and resource-scarce environment. We argue that approaches leveraging Value-of-Information (VoI) concepts and tools are particularly interesting to support the realization of that objective. This paper describes innovative methodologies and reference models for the service fabric management of fog computing services. First, we formalize the VoI concept and discuss its adoption in fog computing environments. Then, we propose a model that aims at maximizing the allocation of fog services from a value-based perspective. To overcome the complexity of this model, we present two possible solutions (a simplified user-specific VoI model and a distance-based heuristic), and we compare them by adopting meta-heuristics as optimization techniques. Then, we investigate the adoption of a hybrid model, which combines the distance-based heuristic with the simplified user-specific VoI model. Experimental results prove the validity of all presented approaches and highlight the soundness of the distance-based heuristic, which is capable of reaching the 91% performance of the simplified user-specific VoI model in a very short amount of time. This makes it a suitable approach for online optimization of resources in fog computing.

中文翻译：

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基于信息价值的雾服务管理框架

雾计算应用程序的管理是一项具有挑战性的任务，需要处理动态和资源稀缺的环境。我们认为，利用信息价值 (VoI) 概念和工具的方法对于支持该目标的实现特别有趣。本文描述了雾计算服务的服务结构管理的创新方法和参考模型。首先，我们将 VoI 概念形式化并讨论其在雾计算环境中的应用。然后，我们提出了一个模型，旨在从基于价值的角度最大化雾服务的分配。为了克服该模型的复杂性，我们提出了两种可能的解决方案（简化的用户特定 VoI 模型和基于距离的启发式），并通过采用元启发式作为优化技术对它们进行比较。然后，我们研究了混合模型的采用，该模型将基于距离的启发式与简化的用户特定 VoI 模型相结合。实验结果证明了所有提出的方法的有效性，并突出了基于距离的启发式方法的稳健性，它能够在很短的时间内达到简化的用户特定 VoI 模型的 91% 性能。这使其成为雾计算中资源在线优化的合适方法。