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Summary
Summary
A team of recognized experts leads the way to dependable computing systems
With computers and networks pervading every aspect of daily life, there is an ever-growing demand for dependability. In this unique resource, researchers and organizations will find the tools needed to identify and engage state-of-the-art approaches used for the specification, design, and assessment of dependable computer systems.
The first part of the book addresses models and paradigms of dependable computing, and the second part deals with enabling technologies and applications. Tough issues in creating dependable computing systems are also tackled, including:
* Verification techniques
* Model-based evaluation
* Adjudication and data fusion
* Robust communications primitives
* Fault tolerance
* Middleware
* Grid security
* Dependability in IBM mainframes
* Embedded software
* Real-time systems
Each chapter of this contributed work has been authored by a recognized expert. This is an excellent textbook for graduate and advanced undergraduate students in electrical engineering, computer engineering, and computer science, as well as a must-have reference that will help engineers, programmers, and technologists develop systems that are secure and reliable.
Author Notes
HASSAN B. DIAB, PhD, is Professor of Electrical and Computer Engineering, Faculty of Engineering and Architecture, American University of Beirut (AUB). He is currently Dean of the School of Engineering at AUB and Acting President of Dhofar University, Sultanate of Oman. He is the Associate Editor of Simulation: Transactions of the Society for Modeling and Simulation International and a founding member of the Arab Computer Society.
ALBERT Y. ZOMAYA, PhD, is the CISCO Systems Chair Professor of Internetworking, School of Information Technologies, The University of Sydney, and Deputy Director for Information Technology of the Sydney University Biological Informatics and Technology Centre. Dr. Zomaya has been the chair of the IEEE Technical Committee on Parallel Processing and has been awarded the IEEE Computer Society's Meritorious Service Award.
Reviews 1
Choice Review
Computer science defines dependability as the ability to deliver a trusted service and to avoid more frequent and severe failures than are acceptable. Attributes of dependability are availability, reliability, safety, confidentiality, integrity, and maintainability. Threats include faults, errors, and failures. Means to attain dependability include fault prevention, fault tolerance, fault removal, and fault forecasting. The growing reliance on computing systems makes research in and applications of dependability increasingly important. Editors Zomaya (Univ. of Sydney; editor in chief, "Wiley Book Series on Parallel and Distributed Computing," of which the book under review is part) and Diab (American Univ. in Beirut) have produced a solid collection of research papers on the specification, design, and assessment of dependable computer systems. A balance is struck between theoretical papers on fundamentals and practical papers on solutions using case studies, discussions of pros and cons, and lessons learned. Topics encompass verification techniques, tolerating arbitrary failures, robust wireless sensor networks, safety critical systems, dependability evaluation, voting, telemedicine, tracking errors, network resilience, safeguarding critical infrastructures, adaptive metaheuristics for routing, and reconfigurable computing. A foundation work in the field is Dependability: Basic Concepts and Terminology in English, French, German, Italian, and Japanese, ed. by J. C. Laprie (1992). ^BSumming Up: Recommended. Graduate students through professionals. M. Mounts Dartmouth College
Table of Contents
Preface | p. xxiii |
Contributors | p. xxxv |
Acknowledgments | p. xxxix |
Part I Models and Paradigms | p. 1 |
1 Formal Verification Techniques for Digital Systems | p. 3 |
1.1 Introduction | p. 3 |
1.2 Basic Techniques for Formal Verification | p. 4 |
1.3 Verification Techniques for Combinational Circuit Equivalence | p. 7 |
1.4 Verification Techniques for Sequential Circuits | p. 14 |
1.5 Summary | p. 24 |
References | p. 24 |
2 Tolerating Arbitrary Failures With State Machine Replication | p. 27 |
2.1 Introduction | p. 27 |
2.2 System Model | p. 31 |
2.3 Total Order Broadcast | p. 32 |
2.4 Weak Interactive Consistency | p. 36 |
2.5 Muteness Failure Detector | p. 44 |
2.6 Concluding Remarks | p. 52 |
References | p. 55 |
3 Model-Based Evaluation as a Support to the Design of Dependable Systems | p. 57 |
3.1 Introduction | p. 57 |
3.2 The Role of Model-Based Evaluation in the Development of Dependable Systems | p. 58 |
3.3 Dependability Modeling Methodologies and Tools | p. 61 |
3.4 Analytical Modeling to Support Design Decisions | p. 68 |
3.5 Analytical Modeling to Support Fault Removal During Operational Life | p. 76 |
3.6 Summary | p. 82 |
References | p. 82 |
4 Voting: A Paradigm for Adjudication and Data Fusion in Dependable Systems | p. 87 |
4.1 Introduction | p. 87 |
4.2 Voting in Dependable Systems | p. 88 |
4.3 Voting Schemes and Problems | p. 94 |
4.4 Voting for Data Fusion | p. 98 |
4.5 Implementation Issues | p. 102 |
4.6 Unifying Concepts | p. 107 |
4.7 Conclusion | p. 110 |
References | p. 111 |
5 Robust Communication Primitives for Wireless Sensor Networks | p. 115 |
5.1 Introduction | p. 115 |
5.2 Defining Realistic Models | p. 117 |
5.3 Our System Model | p. 119 |
5.4 Permutation Routing in a Single-hop Topology: State-of-the-Art | p. 121 |
5.5 An Energy-Efficient Protocol Using a Low-Power Control Channel | p. 125 |
5.6 Our Routing Protocol for a Faulty Network | p. 132 |
5.7 Our Generalized Protocol for a Multichannel Network | p. 135 |
5.8 Concluding Remarks | p. 140 |
References | p. 140 |
6 System-Level Diagnosis and Implications in Current Context | p. 143 |
6.1 Issues in Large and Complex Computing Systems | p. 143 |
6.2 System-Level Diagnosis | p. 145 |
6.3 Classification of Diagnosable Systems | p. 148 |
6.4 Diagnosability Algorithms | p. 157 |
6.5 Diagnosis Algorithms | p. 160 |
6.6 Application of System-Level Diagnosis Algorithm | p. 165 |
6.7 Summary and Conclusions | p. 166 |
References | p. 167 |
7 Predicate Detection in Asynchronous Systems With Crash Failures | p. 171 |
7.1 Introduction | p. 171 |
7.2 Predicate Detection in Fault-Free Environments | p. 173 |
7.3 Failures and Failure Detection | p. 177 |
7.4 Predicate Detection in Faulty Environments | p. 183 |
7.5 Solving Predicate Detection in Faulty Environments | p. 194 |
7.6 Conclusion | p. 209 |
References | p. 211 |
8 Fault Tolerance Against Design Faults | p. 213 |
8.1 Introduction | p. 213 |
8.2 Examples and Principles | p. 215 |
8.3 Potential and Actual Benefits | p. 225 |
8.4 Design Solutions | p. 230 |
8.5 Summary | p. 236 |
References | p. 238 |
9 Formal Methods for Safety Critical Systems | p. 243 |
9.1 Introduction | p. 243 |
9.2 Specification of Safety | p. 245 |
9.3 Historical Background | p. 247 |
9.4 Safety | p. 248 |
9.5 Application Areas | p. 253 |
9.6 Specification Framework | p. 256 |
9.7 System State and Behavior | p. 262 |
9.8 Discussion | p. 265 |
9.9 Conclusion | p. 268 |
References | p. 269 |
Part II Enabling Technologies and Applications | p. 273 |
10 Dependability Support in Wireless Sensor Networks | p. 275 |
10.1 Motivation and Background | p. 276 |
10.2 Service Centric Model | p. 279 |
10.3 Conclusion | p. 283 |
References | p. 283 |
11 Availability Modeling in Practice | p. 285 |
11.1 Introduction | p. 285 |
11.2 Modeling Approaches | p. 286 |
11.3 Composite Availability and Performance Model | p. 292 |
11.4 Digital Equipment Corporation Case Study | p. 297 |
11.5 Conclusion | p. 315 |
References | p. 315 |
12 Experimental Dependability Evaluation | p. 319 |
12.1 Field Measurement | p. 321 |
12.2 Fault Injection | p. 323 |
12.3 Robustness Testing | p. 337 |
12.4 Recent Developments: Dependability Benchmarking | p. 340 |
12.5 Conclusion | p. 342 |
References | p. 343 |
13 A Dependable Architecture for Telemedicine in Support of Disaster Relief | p. 349 |
13.1 Introduction | p. 349 |
13.2 Telemedicine-State of the Art | p. 350 |
13.3 The WIRM System Architecture | p. 352 |
13.4 A Novel 3D Data Compression Technique | p. 356 |
13.5 Interactive Remote Visualization | p. 358 |
13.6 An Overview of H3M-Our Wireless Architecture | p. 359 |
13.7 Concluding Remarks | p. 366 |
References | p. 366 |
14 An Overview of IBM Mainframe Dependable Computing: From System/360 to Series | p. 369 |
14.1 Introduction | p. 369 |
14.2 Error Detection and Fault Isolation | p. 375 |
14.3 Instruction Level Retry | p. 380 |
14.4 Online Repair | p. 386 |
14.5 Summary | p. 391 |
References | p. 392 |
15 Tracking the Propagation of Data Errors in Software | p. 395 |
15.1 Introduction | p. 395 |
15.2 Target System Model | p. 396 |
15.3 Overview of the Tool Suite | p. 397 |
15.4 Setup: Experiment Design and Target Instrumentation | p. 401 |
15.5 Injection: Running Experiments | p. 407 |
15.6 Analysis: Obtaining Error Propagation Characteristics | p. 408 |
15.7 Example Results Generated by Propane | p. 409 |
15.8 Propane's Attributes and Main Characteristics | p. 414 |
15.9 Summary | p. 415 |
References | p. 416 |
16 Integrated Reliable Real-Time Systems | p. 419 |
16.1 Background | p. 421 |
16.2 Integration Issues | p. 425 |
16.3 Few Forward Steps | p. 429 |
16.4 An Example Aerospace Application | p. 432 |
16.5 Conclusion | p. 442 |
References | p. 443 |
17 Network Resilience by Emergent Behavior from Simple Autonomous Agents | p. 449 |
17.1 Introduction | p. 449 |
17.2 Network Resilience | p. 450 |
17.3 Handling Routing and Resources in Networks by Emergence | p. 457 |
17.4 Cross-Entropy Based Path Finding | p. 460 |
17.5 Finding "Best-Effort" Primary/Backup Paths | p. 468 |
17.6 Discussion | p. 473 |
17.7 Concluding Remarks | p. 475 |
References | p. 475 |
18 Safeguarding Critical Infrastructures | p. 479 |
18.1 Introduction | p. 479 |
18.2 Attacks, Failures, and Accidents | p. 480 |
18.3 Solutions | p. 483 |
18.4 The Safeguard Architecture | p. 486 |
18.5 Future Work | p. 497 |
18.6 Conclusion | p. 497 |
References | p. 498 |
19 Impact of Traffic Self-Similarity on the Performance of Routing Algorithms in Multicomputer Systems | p. 501 |
19.1 Introduction | p. 502 |
19.2 The k-ary n-Cube and Dimension-Ordered Routing | p. 504 |
19.3 Modeling of Traffic Self-Similarity | p. 506 |
19.4 The Analytical Model | p. 507 |
19.5 Impact of Self-Similar Traffic on Routing Performance | p. 518 |
19.6 Conclusions | p. 519 |
References | p. 520 |
Appendix 19.1 Notation | p. 523 |
20 Some Observations on Adaptive Meta-Heuristics for Routing in Datagram Networks | p. 525 |
20.1 Introduction | p. 525 |
20.2 The Routing Problem | p. 526 |
20.3 Genetic Algorithms and Routing | p. 532 |
20.4 Genetic Routing Protocol Design | p. 536 |
20.5 Genetic Routing Protocol Implementation | p. 547 |
20.6 Results and Analysis | p. 552 |
20.7 Conclusions | p. 560 |
References | p. 561 |
21 Reconfigurable Computing for Cryptography | p. 563 |
21.1 Introduction | p. 564 |
21.2 Reconfigurable Computing | p. 565 |
21.3 AES Cryptography | p. 576 |
21.4 Case Study: The Twofish Cipher on a Dynamic RC System | p. 579 |
21.5 Future of RC | p. 589 |
21.6 Conclusion | p. 590 |
References | p. 591 |
22 Dependability of Reconfigurable Computing | p. 597 |
22.1 FPGA Preliminaries | p. 598 |
22.2 FPGA Fault Taxonomy | p. 603 |
22.3 Handling FPGA Failures | p. 608 |
22.4 Conclusion and Open Issues | p. 621 |
References | p. 622 |
Index | p. 627 |