论文标题
表征和识别云的移动网络性能瓶颈
Characterization and Identification of Cloudified Mobile Network Performance Bottlenecks
论文作者
论文摘要
这项研究是第一次尝试实验探索5G移动网络可以体验到的性能瓶颈的范围。为此，我们利用了用原型测试台获得的广泛测量，该测试台捕获了云的移动网络的关键方面。我们研究了指标的相关性和多种方法，以准确有效地识别网络架构的不同位置和系统体系结构层的瓶颈。我们的发现验证了多层体系结构中此任务的复杂性，并强调了对跨网络层和功能智能融合指标的新颖监视方法的需求。特别是，我们发现分布式分析在瓶颈识别精度以及产生的计算和通信开销方面都表现出色。
This study is a first attempt to experimentally explore the range of performance bottlenecks that 5G mobile networks can experience. To this end, we leverage a wide range of measurements obtained with a prototype testbed that captures the key aspects of a cloudified mobile network. We investigate the relevance of the metrics and a number of approaches to accurately and efficiently identify bottlenecks across the different locations of the network and layers of the system architecture. Our findings validate the complexity of this task in the multi-layered architecture and highlight the need for novel monitoring approaches that intelligently fuse metrics across network layers and functions. In particular, we find that distributed analytics performs reasonably well both in terms of bottleneck identification accuracy and incurred computational and communication overhead.
