实时应用的分布式计算负载平衡

S. Sthapit, J. Hopgood, J. Thompson
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引用次数: 9

摘要

移动云计算或雾计算是指将计算密集型算法从移动设备卸载到云或中间云,以节省移动设备上的资源(时间和能源)。在本文中,我们将在没有云或雾的情况下寻找替代解决方案。我们使用队列网络对传感器进行建模,并使用线性规划进行调度决策。然后,我们提出了新的算法,可以提高整个系统的效率。结果表明,以使用一些额外的能量为代价,显著提高了性能。特别是,当进入的工作率较高时,我们发现我们的主动集中式系统在性能和能量之间提供了最佳折衷,而当工作率较低时,被动分布式系统更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed computational load balancing for real-time applications
Mobile Cloud Computing or Fog computing refer to offloading computationally intensive algorithms from a mobile device to a cloud or a intermediate cloud in order to save resources (time and energy) in the mobile device. In this paper, we look at alternative solution when the cloud or fog is not available. We modelled sensors using network of queues and use linear programming to make scheduling decisions. We then propose novel algorithms which can improve efficiency of the overall system. Results show significant performance improvement at the cost of using some extra energy. Particularly, when incoming job rate is higher, we found our Proactive Centralised gives the best compromise between performance and energy whereas Reactive Distributed is more effective when job rate is lower.
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