FBRC: Optimization of task Scheduling in Fog-Based Region and Cloud

D. Hoang, T. Dang
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引用次数: 58

Abstract

Fog computing preserves benefits of cloud computing and is strategically positioned to address effectively many local and performance issues because its resources and specific services are virtualized and located at the edge of the customer premises. Resource management is a critical issue affecting system performance significantly. Due to the complex distribution and high mobility of fog devices, computation resources still experience high latencies in fog's large coverage area. This paper considers a Fog-based Region and Cloud (FBRC) in which requests are locally handled not just by a region but multiple regions when additional resources are needed. An efficient task scheduling mechanism is thus essential to minimize the completion time of tasks and improve user experiences. To this end, two issues are investigated in the paper: 1) designing a fog-based region architecture to provide nearby computing resources; 2) investigating efficient scheduling algorithms to distribute tasks among regions and remote clouds. To deal with the complexity of scheduling tasks, a heuristic-based algorithm is proposed based on our formulation and validated by extensive simulations.
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FBRC:基于雾域和云的任务调度优化
雾计算保留了云计算的优点,并且战略性地定位于有效地解决许多本地和性能问题,因为它的资源和特定服务是虚拟化的,并且位于客户场所的边缘。资源管理是影响系统性能的关键问题。由于雾设备分布复杂,移动性高,在雾覆盖面积大的情况下,计算资源仍然存在较高的延迟。本文考虑了一种基于雾的区域和云(FBRC),当需要额外的资源时,请求不仅由一个区域本地处理,而且由多个区域本地处理。因此,有效的任务调度机制对于最小化任务完成时间和改善用户体验至关重要。为此,本文研究了两个问题:1)设计一种基于雾的区域架构,以提供附近的计算资源;2)研究在区域和远程云之间分配任务的有效调度算法。针对任务调度的复杂性,在此基础上提出了一种启发式算法,并通过大量仿真验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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