Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Design and Implementation of an SAN System Based on the Fiber Channel Protocol
IEEE Transactions on Computers
Zodiac: efficient impact analysis for storage area networks
FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
International Journal of Computer Applications in Technology
SIMCAN: a SIMulator framework for computer architectures and storage networks
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
Distributed storage cluster design for remote mirroring based on storage area network
Journal of Computer Science and Technology
New techniques for simulating high performance MPI applications on large storage networks
The Journal of Supercomputing
A component-based end-to-end simulation of the Linux file system
Software and Systems Modeling (SoSyM)
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Storage Area Networks (SANs) are an emerging data communications platform, which interconnects servers and storage devices (such as disks, disk arrays, and tape drives) to create a pool of storage that users can access directly. This networking approach reports benefits such as computer clustering, topological flexibility, fault tolerance, high availability, and remote management.In order to evaluate the performance of these systems it is necessary to have the adequate tools. Usually, performance evaluation may be based on analytical modeling or simulation. Each of them differs in their scope and applicability. However, the simulation modeling technique offers more freedom, flexibility, and accuracy than the analytical methods. Thus, when evaluating the performance of SANs, simulation modeling should be used.In this paper, the issues involved in the modeling and design of a very flexible and easy to use SAN simulator are presented. This tool is able to consider, among others, both real-world I/O traces and synthetic I/O traffic, message paquetization, faults in links and switches, virtual channels, different routing algorithms, etc. We describe its main internal organization, the basic modeling mechanisms the simulator is based on, and the main input parameters and output performance variables. In addition, the analysis of preliminary results using I/O traces is presented, showing that the storage network increases self-similarity of the traffic received by servers, latency variations are more important for control messages than for data messages, and links have a low utilization.