Sorrento: Toward a Self-Organizing Storage Cluster
Project Overview
The goal of the Sorrento project
is to build a self-organizing storage system upon the
cluster architecture, with emphases on four aspects:
programmability, manageability,
performance, and availability.
Clusters provide a cost-effective computing platform,
and incremantal scalability. Sorrento is built upon
the cluster architecture and aims to provide more efficient
usage of storage devices and I/O bandwidth.
Sorrento is designed for cluster applications that need to access large amounts of
data and whose working set does not fit into the memory. Internet services, data mining,
stream-media services are among the applications that can benefit from such a system.
Selected Publications
- Hong Tang, Aziz Gulbeden, Jingyu Zhou, William Strathearn, Tao Yang, and Lingkun Chu.
A Self-Organizing Storage Cluster for Parallel Data-Intensive Applications
To appear in Proceedings of SC2004: High Performance Computing, Networking and Storage Conference, Pittsburgh PA, November 2004
- Hong Tang, Aziz Gulbeden, Jingyu Zhou, Lingkun Chu, and Tao Yang
Sorrento: A Self-Organizing Storage Cluster for Parallel Data-Intensive Applications
Technical Report 2003-30, UCSB, September 2003. (This is an extended version of the SC2004 paper.)
- Hong Tang, and Tao Yang.
An efficient data location protocol for self-organizing storage clusters.
In Proceedings of the International Conference for High Performance Computing and Communications (formerly known as SuperComputing), 2003. One of the five best student paper nominees. [Presentation slides (PDF)]
- Hong Tang and Tao Yang.
Differentiated object placement and location for self-organizing storage clusters.
Technical Report 2002-32, UCSB, November 2002.
People
This project is partially supported by NSF and
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