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Bandwidth estimation for virtual networks
Cloud computing is transforming a large part of IT industry, as evidenced by the increasing popularity of public cloud computing services, such as Amazon Web Service, Google Cloud Platform, Microsoft Windows Azure, and Rackspace Public Cloud. Many cloud computing applications are bandwidth-intensive, and thus the network bandwidth information of clouds is important for their users to manage and troubleshoot the application performance. The current bandwidth estimation methods originally developed for the traditional Internet, however, face great challenges in clouds due to virtualization that is the main enabling technique of cloud computing. First, virtual machine scheduling, which is an important component of computer virtualization for processor sharing, interferes with packet time-stamping and thus corrupts the network bandwidth information carried by the packet timestamps. Second, rate limiting, which is a basic building block of network virtualization for bandwidth sharing, shapes the network packets and thus complicates the bandwidth analysis of the packets. In this dissertation, we tackle the two virtualization challenges to design new bandwidth estimation methodologies for clouds. First, we design bandwidth estimation methods for networks with rate limiting, which is widely used in cloud networks. Bandwidth estimation for networks with token bucket shapers (i.e., a basic type of rate limiters) has been studied before, and the conclusion is that “both capacity and available bandwidth measurement are challenging because of the dichotomy between the raw link bandwidth and the token bucket rate”. Our methods are based on in-depth analysis of the multi-modal distributions of measured bandwidths. Second, we expand the design space of bandwidth estimation methods to challenging but not rare networks where accurate and correct packet time information are hard to obtain, such as in cloud networks with heavy virtual machine scheduling. Specifically, we design and develop a fundamentally new class of sequence-based bandwidth comparison methods that relatively compare the bandwidth information of multiple paths instead of accurately estimating the bandwidth information of a single path. By doing so, our methods use only packet sequence information but not packet time information, and are fundamentally different from the current bandwidth estimation methods that all use packet time information. Furthermore, we design and develop a new class of sequence-based bandwidth estimation methods by conveying the time information in the packet sequence. Sequence-based bandwidth estimation methods estimate the bandwidth information of a path using the time information conveyed in the packet sequence from another path.
Zhang, Ertong, "Bandwidth estimation for virtual networks" (2015). ETD collection for University of Nebraska - Lincoln. AAI3738570.