Practical system reliability

Written by a panel of authors with a wealth of industry experience, the methods and concepts presented here give readers a solid understanding of modeling and managing system and software availability and reliability through the development of real applications and products. The modeling and prediction techniques and tools are customer-focused and data-driven, and are also aligned with industry standards (Telcordia, TL 9000, ISO, etc.). Readers will get a clear understanding about what real-world reliability and availability mean through step-by-step discussions of:

System availability Conceptual model of reliability and availability Why availability varies between customers Modeling availability Estimating parameters and availability from field data Estimating input parameters from laboratory data Estimating input parameters in the architecture/design stage Prediction accuracy Connecting the dots

This book can be used by system architects, engineers, and developers to better understand and manage the reliability/availability of their products; quality engineers to grasp how software and hardware quality relate to system availability; and engineering students as part of a short course on system availability and software reliability.

Author Notes

Eric Bauer is a manager of reliability engineering in Alcatel-Lucent's wireline business in Murray Hill, New Jersey. He has designed, modeled, and analyzed reliability for many different products and solutions, and architected and developed software for a variety of communications devices, platforms, and products.
Xuemei Zhang, PhD, is a principal member of the technical staff in the Network Design and Performance Analysis Department at ATT Labs. She has been working on reliability and performance analysis of wireline-and wireless communications systems and networks. Her major work and research areas are in system and architectural reliability and performance modeling, and software reliability.
Douglas A. Kimber retired from Alcatel-Lucent as a staff reliability engineer. Throughout his career at Bell Labs, Lucent Technologies, and Alcatel-Lucent, he developed high reliability hardware and software platforms, applications, and systems, and then transitioned to reliability engineering where he did reliability modeling and analysis.

Preface	p. xi
Acknowledgments	p. xiii
1 Introduction	p. 1
2 System Availability	p. 5
2.1 Availability, Services and Elements	p. 6
2.2 Classical View	p. 8
2.3 Customers' View	p. 9
2.4 Standards View	p. 10
3 Conceptual Model of Reliability and Availability	p. 15
3.1 Concept of Highly Available Systems	p. 15
3.2 Conceptual Model of System Availability	p. 17
3.3 Failures	p. 19
3.4 Outage Resolution	p. 23
3.5 Downtime Budgets	p. 26
4 Why Availability Varies Between Customers	p. 31
4.1 Causes of Variation in Outage Event Reporting	p. 31
4.2 Causes of Variation in Outage Duration	p. 33
5 Modeling Availability	p. 37
5.1 Overview of Modeling Techniques	p. 38
5.2 Modeling Definitions	p. 58
5.3 Practical Modeling	p. 69
5.4 Widget Example	p. 78
5.5 Alignment with Industry Standards	p. 89
6 Estimating Parameters and Availability from Field Data	p. 95
6.1 Self-Maintaining Customers	p. 96
6.2 Analyzing Field Outage Data	p. 96
6.3 Analyzing Performance and Alarm Data	p. 106
6.4 Coverage Factor and Failure Rate	p. 107
6.5 Uncovered Failure Recovery Time	p. 108
6.6 Convered Failure Detection and Recovery Time	p. 109
7 Estimating Input Parameters from Lab Data	p. 111
7.1 Hardware Failure Rate	p. 111
7.2 Software Failure Rate	p. 114
7.3 Coverage Factors	p. 129
7.4 Timing Parameters	p. 130
7.5 System-Level Parameters	p. 132
8 Estimating Input Parameters in the Architecture/Design Stage	p. 137
8.1 Hardware Parameters	p. 138
8.2 System-Level Parameters	p. 146
8.3 Sensitivity Analysis	p. 149
9 Prediction Accuracy	p. 167
9.1 How Much Field Data Is Enough?	p. 168
9.2 How Does One Measure Sampling and Prediction Errors?	p. 172
9.3 What Causes Prediction Errors?	p. 173
10 Connecting the Dots	p. 177
10.1 Set Availability Requirements	p. 179
10.2 Incorporate Architectural and Design Techniques	p. 179
10.3 Modeling to Verify Feasibility	p. 206
10.4 Testing	p. 208
10.5 Update Availability Prediction	p. 208
10.6 Periodic Field Validation and Model Update	p. 208
10.7 Building an Availability Roadmap	p. 209
10.8 Reliability Report	p. 210
11 Summary	p. 213
Appendix A System Reliability Report outline	p. 216
1 Executive Summary	p. 215
2 Reliability Requirements	p. 217
3 Unplanned Downtime Model and Results	p. 217
Annex A Reliability Definitions	p. 219
Annex B References	p. 219
Annex C Markov Model State-Transition Diagrams	p. 220
Appendix B Reliability and Availability Theory	p. 221
1 Reliability and Availability Definitions	p. 221
2 Probability Distributions in Reliability Evaluation	p. 228
3 Estimation of Confidence Intervals	p. 237
Appendix C Software Reliability Growth Models	p. 245
1 Software Characteristic Models	p. 245
2 Nonhomogeneous Poisson Process Models	p. 246
Appendix D Acronyms and Abbreviations	p. 263
Appendix E Bibliography	p. 265
Index	p. 279
About the Authors	p. 285

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