Along with the development of connected devices and smart environments, the Internet of Things (IoT) has been receiving attention for years because of the growth in the number of devices. It enables a new breed of services and applications expected to analyze and augment captured data from IoT devices in order to create meaningful information for end-users. Due to the limitations of computing and storage on devices, cloud computing is considered as a promising computing paradigm, which can provide elastic resources to the IoT services and applications. In this paper, we investigate the problem of IoT devices deployment in Cloud-Fog system to provide the maximum operation time under the battery constraint of IoT devices. We formulate the problem using a Linear Programming (LP) model taking into account the characteristics of energy resources in Cloud-Fog system as well as the IoT services-specific requirements under two situations with and without battery constraints of the Fog Node devices. As the solution from the LP model might be too complicated for small devices, we propose a heuristic algorithm for solving the problem. The experimental results show that our proposed heuristic solution is very close to optimum solution in terms of energy efficiency.

中文翻译：

---

基于物联网设备能量的云雾系统设计

随着互联设备和智能环境的发展，物联网 (IoT) 由于设备数量的增长，多年来一直受到关注。它支持一种新的服务和应用程序，有望分析和增强从物联网设备捕获的数据，以便为最终用户创建有意义的信息。由于设备上计算和存储的限制，云计算被认为是一种很有前途的计算范式，它可以为物联网服务和应用程序提供弹性资源。在本文中，我们研究了物联网设备在 Cloud-Fog 系统中的部署问题，以在物联网设备的电池限制下提供最长的运行时间。我们使用线性规划 (LP) 模型制定问题，同时考虑到 Cloud-Fog 系统中的能源特性以及在有和没有雾节点设备电池限制的两种情况下物联网服务的特定要求。由于 LP 模型的解决方案对于小型设备可能过于复杂，因此我们提出了一种启发式算法来解决该问题。实验结果表明，我们提出的启发式解决方案在能源效率方面非常接近最优解决方案。