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Storage Network Performance Analysis

ISBN: 978-0-7645-1685-6
432 pages
May 2003
Storage Network Performance Analysis (076451685X) cover image
  • Features vendor-neutral coverage applicable to any storage network
  • Includes a special case-study section citing real-world applications and examples
  • The first vendor-neutral volume to cover storage network performance tuning and optimization
  • Exacting performance monitoring and analysis maximizes the efficiency and cost-effectiveness of existing storage networks
  • Meets the needs of network administrators, storage engineers, and IT professionals faced with shrinking budgets and growing data storage demands
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Part I: Performance Analysis Techniques.

Chapter 1: Introduction to Storage Networking Performance.

Chapter 2: Data Analysis Review.

Chapter 3: Analytic Modeling.

Chapter 4: Simulation Modeling.

Chapter 5: Experimental Analysis.

Part II: Performance Analysis and Modeling of Storage System Components.

Chapter 6: Modeling Storage Devices.

Chapter 7: Modeling Storage Interconnects.

Chapter 8: Modeling Storage Networks.

Chapter 9: Modeling Storage Workloads.

Part III: Storage Performance Engineering.

Chapter 10: Storage Quality of Service.

Chapter 11: Storage Capacity Planning.

Part IV: Storage Performance Tools.

Chapter 12: Storage Benchmarks.

Chapter 13: Performance Management and Monitoring Tools.

Part V: Storage Performance Tuning.

Chapter 14: Host System Tuning.

Chapter 15: Application Tuning.

Chapter 16: Storage Subsystem Tuning.

Chapter 17: Storage Network Tuning.

Part VI: Case Studies.

Chapter 18: Simulating Network Attached Storag e Performance.

Chapter 19: Modeling Remote Storage Replication Performance.

Chapter 20: Web and E-Commerce Data Center Performance Analysis.

Appendix: Glossary of Terms and Acronyms.


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HUSEYIN SIMITCI, PhD, is an engineering researcher at XIOtech Corporation and the author of several research papers devoted to high performance input/output systems and adaptive techniques in parallel file systems. His work contributed to the Scalable I/O Initiative and NSF-funded Grand Challenge programs.
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