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Design and Analysis of Deadline and Budget Constrained Autoscaling (DBCA) Algorithm for 5G Mobile Networks

机译:5G移动网络的期限和预算约束自动缩放(DBCA)算法的设计与分析

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In cloud computing paradigm, virtual resource autoscaling approaches have been intensively studied recent years. Those approaches dynamically scale in/out virtual resources to adjust system performance for saving operation cost. However, designing the autoscaling algorithm for desired performance with limited budget, while considering the existing capacity of legacy network equipment, is not a trivial task. In this paper, we propose a Deadline and Budget Constrained Autoscaling (DBCA) algorithm for addressing the budget-performance tradeoff. We develop an analytical model to quantify the tradeoff and cross-validate the model by extensive simulations. The results show that the DBCA can significantly improve system performance given the budget upper-bound. In addition, the model provides a quick way to evaluate the budget-performance tradeoff and system design without wide deployment, saving on cost and time.
机译:在云计算范例中,近年来已经对虚拟资源自动扩展方法进行了深入研究。这些方法可动态扩展/扩展虚拟资源,以调整系统性能以节省运营成本。然而,在考虑到传统网络设备的现有容量的同时,以有限的预算为期望的性能设计自动缩放算法并不是一件容易的事。在本文中,我们提出了期限和预算约束自动缩放(DBCA)算法,以解决预算绩效之间的权衡问题。我们开发了一个分析模型来量化权衡,并通过广泛的仿真对模型进行交叉验证。结果表明,在预算上限的情况下,DBCA可以显着提高系统性能。此外,该模型提供了一种快速评估预算性能折衷和系统设计的方法,而无需广泛部署,从而节省了成本和时间。

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