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Dynamic Resource Provisioning for Energy Efficient Cloud Radio Access Networks

机译:节能云无线电接入网络动态资源配置

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Energy saving is critical for the cloud radio access networks (C-RANs), which are composed by massive radio access units (RAUs) and energy-intensive computing units (CUs) that host numerous virtual machines (VMs). We attempt to minimize the energy consumption of C-RANs, by leveraging the RAU sleep scheduling and VM consolidation strategies. We formulate the energy saving problem in C-RANs as a joint resource provisioning (JRP) problem of the RAUs and CUs. Since the active RAU selection is coupled with the VM consolidation, the JRP problem shares some similarities with a special bin-packing problem. In this problem, the number of items and the sizes of items are correlated and are both adjustable. No existing method can be used to solve this problem directly. Therefore, we propose an efficient low-complexity algorithm along with a context-aware strategy to dynamically select active RAUs and consolidate VMs to CUs. In this way, we can significantly reduce the energy consumption of C-RANs, while do not incur too much overhead due to VM migrations. Our proposed scheme is practical for a large-size network, and its effectiveness is demonstrated by the simulation results.
机译:节能对于云无线电接入网络(C-RAN)至关重要,由大规模无线电接入单元(RAU)和托管众多虚拟机(VM)的能量密集的计算单元(CU)组成。我们试图通过利用RAU睡眠调度和VM整合策略来最大限度地减少C-RAN的能源消耗。我们将C-RAN中的节能问题作为RAUS和CUS的联合资源供应(JRP)问题。由于活跃的RAU选择与VM整合耦合,JRP问题与特殊的垃圾箱问题分享了一些相似之处。在此问题中,项目的项目数量和大小是相关的,并且都是可调的。没有现有的方法可用于直接解决此问题。因此,我们提出了一种高效的低复杂性算法以及上下文感知策略,以动态选择活动RAU并将VMS合并到CU。通过这种方式,我们可以显着降低C-RAN的能量消耗,而由于VM迁移,不会产生过多的开销。我们所提出的方案对于大型网络实用,其有效性由模拟结果证明。

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