-
- Jie Zheng
- Rice University, Houston, USA
-
- Tze Sing Eugene Ng
- Rice University, Houston, USA
-
- Kunwadee Sripanidkulchai
- National Electronics and Computer Technology Center, Pathumthani, Thailand
書誌事項
- 公開日
- 2011-03-09
- 権利情報
-
- https://www.acm.org/publications/policies/copyright_policy#Background
- DOI
-
- 10.1145/2007477.1952700
- 公開者
- Association for Computing Machinery (ACM)
この論文をさがす
説明
<jats:p>The 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 paper 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 fully implemented system on KVM and a trace-driven framework, we show that our algorithm provides large performance benefits across a wide range of popular virtual machine workloads.</jats:p>
収録刊行物
-
- ACM SIGPLAN Notices
-
ACM SIGPLAN Notices 46 (7), 133-144, 2011-03-09
Association for Computing Machinery (ACM)
