Fog computing is emerging as a new paradigm to deal with latency-sensitive applications, by making data processing and analysis close to their source. Due to the heterogeneity of devices in the fog, it is important to devise novel solutions which take into account the diverse physical resources available in each device to efficiently and dynamically distribute the processing. In this paper, we propose a resource representation scheme which allows exposing the resources of each device through Mobile Edge Computing Application Programming Interfaces (MEC APIs) in order to optimize resource allocation by the supervising entity in the fog. Then, we formulate the resource allocation problem as a Lyapunov optimization and we discuss the impact of our proposed approach on latency. Simulation results show that our proposed approach can minimize latency and improve the performance of the system.
翻译:通过使数据处理和分析接近其源头,雾计算正在成为处理对潜伏敏感的应用的新范例。由于雾中的装置各异,必须设计新的解决办法,考虑到每个装置现有的各种物质资源,以便高效率和动态地分配处理过程。在本文件中,我们提出了一个资源代表方案,通过移动边缘电子应用程序设计接口(MEC APIs)暴露每个装置的资源,以便优化监督实体在雾中的资源分配。然后,我们把资源分配问题发展成一种Lyapunov优化,我们讨论我们所提议的办法对延时的影响。模拟结果表明,我们拟议的办法可以最大限度地减少延时,改善系统的性能。