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FBRC: Optimization of task scheduling in Fog-based Region and Cloud

机译:FBRC:基于FOG的地区和云中的任务调度优化

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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.
机译:雾计算保留云计算的好处,并在战略上定位,以有效地解决许多本地和性能问题,因为其资源和特定服务是虚拟化的,并位于客户场所的边缘。资源管理是一个影响系统性能的重要问题。由于复杂的分布和雾设备的高流动性,计算资源仍然在雾的大覆盖区域中体验高延迟。本文考虑了基于迷的地区和云(FBRC),其中不仅仅是在需要额外资源时本地处理的请求,而不是多个区域。因此,有效的任务调度机制是必不可少的,以最小化任务的完成时间并改善用户体验。为此,本文研究了两个问题:1)设计基于迷雾的地区架构,以提供附近的计算资源; 2)调查高效的调度算法,以在地区和远程云之间分配任务。为了处理调度任务的复杂性,基于我们的配方提出了一种基于启发式的算法,并通过广泛的模拟验证。

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