2020 Theses Doctoral

Understanding Cloud Network Performance

Arnold, Todd W.

Our daily lives are increasingly reliant on Internet-based services, which in turn are increasingly dependent upon a small number of cloud providers to support their functionality. Internet service consolidation aggrandizes the select few cloud providers who are consolidation’s beneficiaries. As cloud providers’ networks – primarily those of Amazon, Google, IBM, and Microsoft – become more vital to the Internet’s operation and functionality, it is paramount that we understand the different factors that affect their performance and how they are affecting the greater Internet. It is also imperative that researchers are able to conduct independent measurements and tests regarding these topics without requiring collaboration with, or special access from, the cloud providers. Due to proprietary implementations, the results of collaborative studies or experiments lack transparency and are difficult, if not impossible, for independent researchers to repeat.

In this dissertation we seek to understand how the cloud providers’ networks impact Internet user performance versus using the public Internet and how they are affecting the Internet’s topological structure. To achieve this, first we enable future research to test how various net- work component interactions affect performance by creating a testbed that approximates the cloud providers’ network environment. The testbed provides researchers with the same control and fidelity as the operators of a complex network, such as the cloud providers. No prior work provided such a platform for Internet networking research.

Second, we examine how the cloud providers’ private Wide Area Networks (WANs) impact user performance. We do this by leveraging new services provided by Google and Amazon which enables us to isolate the latency differences between using their private WANs versus us- ing the public Internet. We conduct the first comprehensive study that quantifies the performance difference, sourced from networks we estimate to represent 91% of the Internet’s user population. We then examine several case studies in specific regions where one of the two networks provides significant performance benefits and examine why these outliers occur. This body of work shows that using only measurements and analyses that do not require special access or permissions from the cloud providers, we can discern that the cloud providers’ private WANs deliver modest performance improvements over the public Internet.

Third, we examine the impact the cloud providers’ networks have on the Internet and its topology. We start by investigating and quantifying to what extent increased connectivity between the cloud providers and other networks allows the cloud providers to bypass the hierarchical Inter- net. We then analyze the geographic deployment strategy of the cloud providers, compare it against the Tier-1 and Tier-2 Internet Service Providers (ISPs), and examine the population coverage of each based on geographic proximity to network resources. We show that the cloud providers’ extensive peering footprints provide the potential for them to reach the majority of networks while bypassing the hierarchical Internet.