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Power Dispatching in Cloud Data Centers Using Smart Microgrids: A Game Theory Approach

机译:使用智能微电网的云数据中心电源分配:一种博弈论方法

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The proliferation of cloud-based applications in smart systems has made the cloud data center a vital and critical part for ensuring a connected world. Due to their energy-hungry servers and huge power facilities, cloud data centers tend to consume a lot of power. In fact, the data centers use about 1.4% of all the power generated on the planet. On one hand, this has a negative impact on the power grid and may cause blackouts. On the other hand, it has a negative impact on the environment and it is mainly involved in global warming. Thus, one of the most important challenges in cloud data centers is power consumption minimization. In this paper, we propose a microgrid-cloud based architecture and study the grid power dispatching problem to cloud data centers. At first, we model the power quantity demand between the data centers and smart microgrids as a non-cooperative game, due to their non-cooperative power demands behavior. Then, we try to allocate the optimal quantity of power to each data center according to its green power consumption, network bandwidth usage and its network equipment power usage. Second, we formulate the game payoff function as a non-linear optimization problem and solve it using Lagrange multipliers and KarushKuhnTucker (KKT) conditions. Finally, we compare the performance of our approach with two power allocation algorithms and showed that our game is more effective and reduces power load with a rate of 40.5%. Furthermore, our scheme incites data centers to use green energy and significantly reduces dioxide carbon emission.
机译:智能系统中基于云的应用程序的激增使云数据中心成为确保互联世界的至关重要的部分。由于其耗能的服务器和庞大的电力设施,云数据中心往往会消耗大量电力。实际上,数据中心使用的能量约占地球上所有发电量的1.4%。一方面,这会对电网造成负面影响,并可能导致停电。另一方面,它对环境有负面影响,并且主要涉及全球变暖。因此,云数据中心最重要的挑战之一就是功耗的最小化。在本文中,我们提出了一种基于微电网-云的架构,并研究了向云数据中心的电网功率分配问题。首先,我们将数据中心和智能微电网之间的电量需求建模为非合作博弈,这是由于它们的非合作电量需求行为。然后,我们尝试根据每个数据中心的绿色功耗,网络带宽使用量和网络设备的电源使用量为每个数据中心分配最优的电量。其次,我们将博弈收益函数公式化为非线性优化问题,并使用拉格朗日乘数和KarushKuhnTucker(KKT)条件对其进行求解。最后,我们将我们的方法与两种功率分配算法的性能进行了比较,结果表明我们的游戏更加有效,并且以40.5%的比率降低了功率负载。此外,我们的计划鼓励数据中心使用绿色能源,并显着减少二氧化碳的排放。

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