Ng, T. S. Eugene2011-07-252011-07-252010Zheng, Jie. "Workload-aware live storage migration for clouds." (2010) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/62053">https://hdl.handle.net/1911/62053</a>.https://hdl.handle.net/1911/62053The emerging open cloud computing model will provide users with great freedom to dynamically migrate virtualized computing services to, from, and between clouds over the wide-area. While this freedom leads to many potential benefits, the running services must be minimally disrupted by the migration. Unfortunately, current solutions for wide-area migration incur too much disruption as they will significantly slow down storage I/O operations during migration. The resulting increase in service latency could be very costly to a business. This thesis presents a novel storage migration scheduling algorithm that can greatly improve storage I/O performance during wide-area migration. Our algorithm is unique in that it considers individual virtual machine's storage I/O workload such as temporal locality, spatial locality and popularity characteristics to compute an efficient data transfer schedule. Using a trace-driven framework, we show that our algorithm provides large performance benefits across a wide range of popular virtual machine workloads.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Computer scienceApplied sciencesThesisTHESIS COMP.SCI. 2010 ZHENG