Minerva: An automated resource provisioning tool for large-scale storage systems
ACM Transactions on Computer Systems (TOCS)
Appia: Automatic Storage Area Network Fabric Design
FAST '02 Proceedings of the Conference on File and Storage Technologies
Hippodrome: Running Circles Around Storage Administration
FAST '02 Proceedings of the Conference on File and Storage Technologies
A Modular, Analytical Throughput Model for Modern Disk Arrays
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
IBM Totalstorage San Volume Controller and San Integration Server
IBM Totalstorage San Volume Controller and San Integration Server
Parameter inference of queueing models for IT systems using end-to-end measurements
Proceedings of the joint international conference on Measurement and modeling of computer systems
Characteristics of I/O traffic in personal computer and server workloads
IBM Systems Journal
A component-based analytical performance model of IP-based SAN
GPC'08 Proceedings of the 3rd international conference on Advances in grid and pervasive computing
A component-based end-to-end simulation of the Linux file system
Software and Systems Modeling (SoSyM)
| Hi-index | 0.00 |
This work explores performance issues of system-level interactions by means of performance modeling. We focus on I/O performance in a storage area network (SAN), namely, the performance of I/O interactions of host servers and storage subsystems via the SAN fabric. We present a component-based simulation performance model, which supports a rich variety of both existing and future storage subsystems, allows for some basic network configurations, and addresses the major I/O aspects of the server operating system. The model's flexibility allows for easy parameter modifications, configuration adjustments, architecture manipulations, and experimentation. The experiments presented in this paper demonstrate some of the ways this model can be utilized, such as data placement, I/O manipulation, and the evaluation of execution alternatives, and shows the types of performance insights that may be gained.