Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the network with low latency and high-access bandwidth to support a diverse range of IoT application scenarios. To fully utilize the potential of this computing paradigm, scalable, adaptive, and accurate scheduling mechanisms and algorithms are required to efficiently capture the dynamics and requirements of users, IoT applications, environmental properties, and optimization targets. This paper presents a taxonomy of recent literature on scheduling IoT applications in Fog computing. Based on our new classification schemes, current works in the literature are analyzed, research gaps of each category are identified, and respective future directions are described.
翻译:雾计算作为一种分布式模式,在网络边缘提供低潜伏和高接入带宽的云类服务,以支持各种IoT应用设想方案。为了充分利用这种计算模式的潜力,需要建立可扩展、适应和准确的排期机制和算法,以便有效捕捉用户的动态和要求、IoT应用、环境属性和优化目标。本文件介绍了最近关于将IoT应用纳入Fog计算日程的文献分类。根据我们的新分类方案,分析了当前文献中的作品,查明了每一类的研究差距,并介绍了各自的未来方向。