云计算的复杂网络方法
A complex network approach to cloud computing
摘要：
云计算已经成为提高计算速度的重要手段。严重影响这种系统性能的一个问题是选择节点作为负责执行用户任务的服务器。在这篇文章中，我们将报告如何使用复杂网络来模拟这样的问题。更具体地说，我们调查的处理性能分别以云系统为基础的Erdos-Renyi和Barabasi-Albert拓扑结构包含两个服务器。在我们的分析中还考虑了涉及两个社区的云网络，这些社区不一定具有相同的规模。每个配置的性能量化的两个指标：用户和最近的服务器之间的通信成本，以及两个服务器之间的任务分配的平衡。关于后一个索引，ER拓扑对于较小的平均度提供比BA情况更好的性能，并且对于较大的平均度提供相反的行为。关于成本，在BA拓扑中发现较小的值，而与平均度无关。此外，我们还验证了在ER中比在BA中更容易找到好的服务器。令人惊讶的是，平衡和成本并没有受到社区存在的太多影响。然而，对于定义良好的社区网络，我们发现将每个服务器分配给不同的社区以实现更好的性能是很重要的。
英文摘要：
Cloud computing has become an important means to speed up computing. One problem influencing heavily the performance of such systems is the choice of nodes as servers responsible for executing the users' tasks. In this article we report how complex networks can be used to model such a problem. More specifically, we investigate the performance of the processing respectively to cloud systems underlain by Erdos-Renyi and Barabasi-Albert topology containing two servers. Cloud networks involving two communities not necessarily of the same size are also considered in our analysis. The performance of each configuration is quantified in terms of two indices: the cost of communication between the user and the nearest server, and the balance of the distribution of tasks between the two servers. Regarding the latter index, the ER topology provides better performance than the BA case for smaller average degrees and opposite behavior for larger average degrees. With respect to the cost, smaller values are found in the BA topology irrespective of the average degree. In addition, we also verified that it is easier to find good servers in the ER than in BA. Surprisingly, balance and cost are not too much affected by the presence of communities. However, for a well-defined community network, we found that it is important to assign each server to a different community so as to achieve better performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
