Virtualization is the cornerstone technology of cloud computing. Advancements in virtualization enable researchers to tackle key challenges in today's cloud. The first part of this thesis delves into the emerging container virtualization and how leveraging containers we address resource management and pricing challenges in the cloud. We try calling for an end to the constant battle between public cloud providers and users over the pricing options of cloud instances: the users generally have to pay for the entire billing cycle even on fractional usage. Ideally, idle cloud instances with residual billing cycle should be resalable by their users. Such trading demands efficient resource consolidation and multiplexing, because the revenue and use cases are confined by the transient nature of the instances. This thesis presents HARV, a novel cloud service that facilitates the management and trade of cloud instances. The platform relies on hybrid virtualization, an infrastructure layout integrating both the hypervisor-based virtual machines and lightweight containers, incorporating a truthful online auction mechanism for instance trading and resource allocation. Our design achieves efficient resource consolidation with no need for provider-level support, and we have deployed a prototype of HARV on the Amazon EC2 public cloud. Our evaluations reveal that applications experience negligible performance overhead when hosted on HARV; trace-driven simulations further show that HARV can achieve substantial cost savings. The second part of the thesis explores the emerging Network Function Virtualization (NFV). Virtualization and cloud computing constitute a major driving force for Internet innovations. In today's Internet, multimedia content traffic accounts for the largest share of all traffic. Downstream towards the consumers, multimedia traffic often traverse through middleboxes, undergoing additional data processing imposed by content distributors. With NFV, middleboxes are embedded in general-purpose, off-the-shelf servers, allowing content distributors to conveniently borrow existing cloud technologies to process traffic. Despite these benefits, we find NFV incurs an undue amount of energy consumption when carrying out high packet forwarding performance. We identify the energy inefficiency issue in the NFV dataplane which can be exacerbated if not handle properly. We outline a power management framework that exploits CPU frequency scaling to save energy.
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Thesis advisor: Liu, Jiangchuan
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