Quantitative assessments of distributed systems : methodologies and techniques

Quantitative assessments of distributed systems : methodologies and techniques / edited by Dario Bruneo and Salvatore Distefano.

"Distributed systems employed in critical infrastructures must fulfill dependability, timeliness, and performance specifications. Since these systems most often operate in an unpredictable environment, their design and maintenance require quantitative evaluation of deterministic and probabilist...

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Bibliographic Details
Other Authors: Bruneo, Dario, Distefano, Salvatore
Format: eBook
Language:English
Published: Hoboken : John Wiley and Sons, Inc., 2015.
Series:Performability engineering series.
Subjects:
Computer systems > Evaluation > Mathematics.
System analysis > Mathematics.
Electronic data processing > Distributed processing > Mathematical models.
Quantitative research.
TECHNOLOGY & ENGINEERING > Electronics > General.
Electronic data processing > Distributed processing > Mathematical models
Quantitative research
Online Access:Click for online access
Table of Contents:
  • Half Title page; Title page; Copyright page; Preface; Part I: Verification; Chapter 1: Modeling and Verification of Distributed Systems Using Markov Decision Processes; 1.1 Introduction; 1.2 Markov Decision Processes; 1.3 Markov Decision Well-Formed Net formalism; 1.4 Case study: Peer-to-Peer Botnets; 1.5 Conclusion; Acknowledgments; Appendix A Well-Formed Net Formalism; References; Chapter 2: Quantitative Analysis of Distributed Systems in Stoklaim: A Tutorial; 2.1 Introduction; 2.2 STOKLAIM: Stochastic KLAIM; 2.3 STOKLAIM Operational Semantics; 2.4 MoSL: Mobile Stochastic Logic.
  • 2.5 jSAM: Java Stochastic Model-Checker2.6 Leader Election in STOKLAIM; 2.7 Concluding Remarks; References; Chapter 3: Stochastic Path Properties of Distributed Systems: The CSLTA Approach; 3.1 Introduction; 3.2 The Reference Formalisms for System Definition; 3.3 The Formalism for Path Property Definition: CSLTA; 3.4 CSLTA at Work: A Fault-Tolerant Node; 3.5 Literature Comparison; 3.6 Summary and Final Remarks; References; Part II: Evaluation; Chapter 4: Failure Propagation in Load-Sharing Complex Systems; 4.1 Introduction; 4.2 Building Blocks; 4.3 Sand Box for Distributed Failures.
  • 4.4 SummaryReferences; Chapter 5: Approximating Distributions and Transient Probabilities by Matrix Exponential Distributions and Functions; 5.1 Introduction; 5.2 Phase Type and Matrix Exponential Distributions; 5.3 Bernstein Polynomials and Expolynomials; 5.4 Application of BEs to Distribution Fitting; 5.5 Application of BEs to Transient Probabilities; 5.6 Conclusions; References; Chapter 6: Worst-Case Analysis of Tandem Queueing Systems Using Network Calculus; 6.1 Introduction; 6.2 Basic Network Calculus Modeling: Per-Flow Scheduling.
  • 6.3 Advanced Network Calculus Modeling: Aggregate Multiplexing6.4 Tandem Systems Traversed by Several Flows; 6.5 Mathematical Programming Approach; 6.6 Related Work; 6.7 Numerical Results; 6.8 Conclusions; References; Chapter 7: Cloud Evaluation: Benchmarking and Monitoring; 7.1 Introduction; 7.2 Benchmarking; 7.3 Benchmarking with mOSAIC; 7.4 Monitoring; 7.5 Cloud Monitoring in mOSAIC's Cloud Agency; 7.6 Conclusions; References; Chapter 8: Multiformalism and Multisolution Strategies for Systems Performance Evaluation; 8.1 Introduction; 8.2 Multiformalism and Multisolution.
  • 8.3 Choosing the Right Strategy8.4 Learning by the Experience; 8.5 Conclusions and Perspectives; References; Part III: Optimization and Sustainability; Chapter 9: Quantitative Assessment of Distributed Networks Through Hybrid Stochastic Modeling; 9.1 Introduction; 9.2 Modeling of Complex Systems; 9.3 Performance Evaluation of KNXnet/IP Networks Flow Control Mechanism; 9.4 LCII: On-Line Risk Estimation of a Power-Telco Network; 9.5 Conclusion; Acknowledgements; References; Chapter 10: Design of it Infrastructures of Data Centers: An Approach Based on Business and Technical Metrics.

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