M. Ajmone Marsan, G. Balbo, G. Conte, S. Donatelli and G. Franceschinis
Modelling with Generalized Stochastic Petri Nets
Wiley Series in Parallel Computing
John Wiley and Sons
ISBN: 0 471 93059 8
THIS BOOK IS OUT OF PRINT.
IT IS NOW POSSIBLE
TO DOWNLOAD A REVISED ELECTRONIC
VERSION (.pdf) OF THE BOOK.
Orders should be sent to:
John Wiley & Sons Ltd Distribution Centre
Southern Cross Trading Estate
1 Oldlands Way
Bognor Regis
West Sussex
PO22 9SA
England
Tel: +44 1243 779777
Fax: +44 1243 820250
Email: market@wiley.co.uk
|
|
|
MODELLING WITH GENERALIZED STOCHASTIC PETRI NETS
M. Ajmone Marsan, Politecnico di Torino, Italy,
G. Balbo, Universita' di Torino, Italy,
G. Conte, Universita' di Parma, Italy,
S. Donatelli, Universita' di Torino, Italy
and G. Franceschinis, Universita' di Torino, Italy
This book presents a unified theory of Generalized Stochastic Petri Nets
(GSPNs) together with a set of illustrative examples from different application
fields.
The continuing success of GSPNs and the increasing interest in using
them as a modelling paradigm for the quantitative analysis of distributed
systems suggested the preparation of this volume with the intent of
providing newcomers to the field with a useful tool for their first
approach.
Readers will find a clear and informal explanation of the concepts
followed by formal definitions when necessary or helpful. The largest
section of the book however is devoted to showing how this methodology
can be applied in a range of domains.
Contents:
- Preface
- 1 INTRODUCTION
- 1.1 Shared Resources
- 1.2 Fork and Join
- 1.3 Kanban Process
- 1.4 Token Ring LAN
- 2 PETRI NETS AND THEIR PROPERTIES
- 2.1 Petri Net Models
- 2.2 Models, Systems, and Nets
- 2.3 System Dynamics
- 2.3.1 Enabling and firing rules
- 2.3.2 Reachability set and reachability graph
- 2.3.3 Modelling issues
- Modelling logical conditions
- 2.3.4 Typical situations in the PN system evolution
- Conflicts
- Concurrency
- Confusion
- Causal connection
- Mutual exclusion
- 2.4 Properties of Petri Nets
- Reachability and reversibility
- Absence of deadlock
- Liveness
- Boundedness
- Mutual exclusion
- 2.5 Structural Analysis Techniques
- 2.5.1 Linear algebraic techniques
- P-semiflows and P-invariant relations
- T-semiflows and T-invariant relations
- 2.5.2 Graph-based structural techniques
- Deadlocks and traps
- Structural relations between transitions
- 2.6 State Space Analysis Techniques
- Reachability
- Reversibility
- Absence of deadlock
- Liveness
- Boundedness
- Mutual exclusion
- Effective conflict and confusion
- 3 TIME IN PETRI NETS
- 3.1 The Motivations for Timing
- 3.2 Timed Transitions
- 3.2.1 Immediate transitions
- 3.2.2 Two examples
- 3.3 Parallelism and Conflict
- 3.4 Memory
- 3.4.1 An example with the enabling memory policy
- 3.4.2 An example with the age memory policy
- 3.5 Multiple Enabling
- 3.6 A Timed PN Model Example
- 3.7 Performance Measures
- 4 PETRI NETS WITH PRIORITY
- 4.1 Definition and Dynamics
- Enabling and firing
- An example
- 4.2 Conflicts, Confusion and Priority
- Conflict
- Confusion and priority
- 4.3 Properties of Priority PN Models
- Reachability
- Boundedness
- Liveness and liveness degree
- Reversibility and home states
- 4.4 Structural Analysis Techniques
- 4.4.1 Linear algebraic techniques
- P- and T-semiflows
- 4.4.2 Graph based analysis
- Structural conflict
- 4.5 Reachability Analysis Techniques
- Reachability graph of PN models with priority
- Reduced reachability graphs
- 5 GSPN BASICS
- 5.1 Exponential Distributions for Transition Delays
- 5.2 Mixing Exponentially Distributed and Null Delays
- 5.3 Some Extensions
- 5.4 The Definition of a GSPN Model
- 5.5 An Example of a GSPN Model
- 5.6 Some Fine Points
- 6 ANALYSIS OF GSPN MODELS
- 6.1 The Stochastic Process Associated with a SPN
- 6.1.1 SPN performance indices
- 6.1.2 An example SPN system
- 6.2 The Stochastic Process Associated with a GSPN
- 6.2.1 Marking dependency
- 6.2.2 An example GSPN system
- 6.3 Numerical Solution of GSPN Systems
- 6.3.1 Evaluation of the steady-state probability distribution for the example GSPN system
- 6.3.2 Performance analysis of the example GSPN
- 6.4 Reducing GSPNs to SPNs
- 6.5 Simulation of GSPN Systems
- 6.5.1 Simulation of the example GSPN system
- 7 GSPN REPRESENTATION OF PHASE-TYPE DISTRIBUTIONS
- 7.1 The Central Server Model Example
- 7.1.1 CPU interruptions
- 7.1.2 CPU memory policies
- 7.2 Phase-Type Distributions
- 7.2.1 Erlang distributions
- 7.2.2 Numerical evaluation
- 7.3 General Phase-Type Distributions
- 8 MODELLING FLEXIBLE MANUFACTURING SYSTEMS
- 8.1 Flexible Manufacturing Systems
- 8.2 A Kanban System
- 8.2.1 Structural analysis of the GSPN model of the Kanban system
- 8.2.2 Performance analysis of the Kanban system
- 8.3 Push Production Systems
- A system using continuous transportation
- A system with AGV transportation
- 8.3.1 Structural analysis of the push production systems
- 8.3.2 Performance analysis of the system with AGV transport
- 9 COMPACT MODELS OF RANDOM PDLLING SYSTEMS
- 9.1 Polling Systems
- 9.2 Modelling Random Polling the Easy Way
- 9.2.1 The first complete random polling model
- 9.3 Beginning to Exploit Symmetries
- 9.3.1 Walking before choosing?
- 9.3.2 Number of states and limitations of the model
- 9.4 Abstracting from the Queue Identifiers
- 9.4.1 The abstract GSPN model
- 9.4.2 Walking before choosing!
- 9.4.3 Number of states and limitations of the model
- 9.5 From GSPNs to SPNs
- 10 MODELLING AND ANALYSIS OF CONCURRENT PROGRAMS
- 10.1 Introduction to the Static Analysis of Concurrent Programs
- 10.2 The Automatic Translation from Programs to GSPNs
- 10.2.1 Languages of interest
- 10.2.2 The translation procedure
- 10.3 An Example of Translation
- 10.4 Modelling Control Variables to Reduce Nonfaults
- 10.5 Stochastic Analysis
- Probability of two communications at the same time
- Joint distribution of p_k and p_n
- Throughput
- Mutual exclusion
- 11 MODELS OF CONCURRENT ARCHITECTURES
- 11.1 Concurrent Architectures
- 11.2 Single Processor Model
- 11.3 Single Processor Model with Multitasking
- 11.4 Models of Mesh Structures
- 11.4.1 Mesh models without multitasking
- 11.4.2 Mesh models with multitasking
- Appendix A: STOCHASTIC PROCESS FUNDAMENTALS
- A.1 Basic Definitions
- A.2 Markov Processes
- A.3 Discrete-Time Markov Chains
- A.3.1 Steady-state distribution
- A.3.2 Matrix formulation
- A.3.3 Example
- A.4 Continuous-Time Markov Chains
- A.4.1 Steady-state distribution
- A.4.2 Matrix formulation
- A.4.3 Sojourn and recurrence times
- A.4.4 The embedded Markov chain
- A.4.5 Example
- A.5 Aggregation of States in Markov Chains
- A.5.1 Aggregation in discrete-time Markov chains
- A.5.2 Aggregation in continuous-time Markov chains
- A.6 Semi-Markov Processes
- A.7 Semi-Markov Reward Processes
- Appendix B: GLOSSARY
- References
- Index