The document discusses best practices and implementation details for discrete-event simulation, emphasizing its advantages over analytic simulations. Key components include the environment, event progression, state, clock, and event list, with practical examples in banking, transportation, and networks. It also provides best practices for coding in Python and Java, highlighting the importance of configuration management, result saving, and the efficient use of threading.

1. BEST PRACTICES IN DISCRETE-
EVENT SIMULATION
CARLOS NATALINO

2. 2020-03-01 Chalmers University of Technology 2
OUTLINE
• Introduction
• Performance analysis
• Discrete-event simulation
• Routing and resource assignment in optical networks
• Implementation details
• Best practices
• Examples in Java and Python
• Conclusions
• Q&A

3. • Performance analysis
2020-03-01 Chalmers University of Technology 3
DISCRETE-EVENT SIMULATION
Analytic Simulation Prototyping
Realistic
Expensive
Prone to contamination
Set of equations
e.g.: queue theory
Set of events described by random numbers
e.g.: event-driven simulation
Real systems and devices
e.g.: testbed

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DISCRETE-EVENT SIMULATION
• Environment
• Models the set of elements that the simulation is interested in
analyzing
• Discrete sequence of events in time
• Each event changes (or may change) the state of the
environment
• No changes between two consecutive events
• Next-time event progression: time between events may vary
(e.g., arrival/departure of requests)
• Fixed-increment time progression: time between events is
fixed (e.g., periodic reconfiguration)

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DISCRETE-EVENT SIMULATION
• Main components:
• State: the environment state at a given point in time
• Clock: the current simulation clock, which is not tied to the wall
clock
• Event list: the list with the next events to be processed/executed
• Events: set of (problem-specific) procedures to be executed
over the environment
Event list
Simulation
clock

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EVENT-DRIVEN SIMULATION
Examples of environments and their events
1. Bank queue
• Productor-consumer kind of problem
• Clients arrive, cashiers serve the clients
• Queue theory can be used for analytic assessment
2. Public transportation
• Passengers boarding/dropping at stops, vehicle speed change, etc.
3. Virus outbreak
• Contact probability between people, contamination probability, etc.
4. Networks
• Packet-based: packet arrival, enqueue, dequeue, departure
• Circuit-based: call arrival, call departure, etc.

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ROUTING AND SPEC. ALLOC. IN OPTICAL NETWORKS
• Circuit-switched network
• Discrete resource allocation
• Wavelength division multiplexing
(WDM)
• Single-wavelength channels
• With wavelength conversion (opaque)
• No wavelength continuity constraint
• Without wavelength conversion (transparent)
• Elastic optical network (EON)
• Multiple-slice channels
• Spectrum continuity and contiguity constraint
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IMPLEMENTATION DETAILS
State
• Can be modeled as a class
• Attributes of the class model the state of the environment
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/core.py#L12
Python
Java
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/components/Topology.java#L21

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IMPLEMENTATION DETAILS
Event list
• Should be implemented as an ordered list
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/core.py#L219
Python
Java
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/Simulator.java#L27

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IMPLEMENTATION DETAILS
Events
• Create a standard event model
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/events.py#L6
Python
Java
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/events/Event.java#L11
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/events/ActiveProcess.java#L12

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IMPLEMENTATION DETAILS
Events
• Create a standard event model and use it
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/core.py#L318
Python
Java
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/Simulator.java#L86

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BEST PRACTICES
Never overwrite files
• Have a base folder for all results of a given batch
• Create a timestamp’d folder for the results of every run
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/run.py#L37 https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/MultiThreadSimulator.java#L94
Python
Java

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BEST PRACTICES
Have file- or argument-based configuration
• Prevents you from recompiling the code
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/run.py#L137 https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/FileAgent.java#L89
Python
Java

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BEST PRACTICES
Bonus: make a copy of the configurations for every result
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/run.py#L45 https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/MultiThreadSimulator.java#L104
Python
Java

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BEST PRACTICES
Bonus 2: make a copy of the current simulator version
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/run.py#L59 https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/MultiThreadSimulator.java#L120
Python
Java

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BEST PRACTICES
x. Only enqueue events when needed
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/events.py#L17 https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/events/ConnectionManager.java#L104
Python
Java

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BEST PRACTICES
Run different configurations in threads
• Single environment can/should not be parallelized
• Multiple environments can/should be parallelized
• Use of thread pool is recommended (improves resource efficiency)
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/run.py#L93 https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/MultiThreadSimulator.java#L131
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/MultiThreadSimulator.java#L152
Python
Java

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BEST PRACTICES
Save averages and individual results
• Bonus: save everything possible
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/core.py#L325
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/run.py#L113
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/Simulator.java#L100
https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/065e0726ffe7e7146616d5347b90c7da21bbf851/src/main/java/simulator/cs/anycast/core/Simulator.java#L122
Python
Java

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BEST PRACTICES
Plot results as you go
• Helps identifying problems before everything runs
https://github.com/carlosnatalino/python-simple-anycast-wdm-simulator/blob/cdb1340234cad0217fc7687abcadb1a3f35c8522/run.py#L103 https://github.com/carlosnatalino/java-anycast-cs-simulator/blob/bbede8fabadcc8c8c96542af469c7334e3ba1a67/src/main/java/simulator/cs/anycast/core/MultiThreadSimulator.java#L174
Python
Java

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CONCLUSIONS AND LINKS
• Simulations are a good compromise between cost, time and
adherence to reality
• Java and Python are both great options to implement your simulator
• Good trade-off between development complexity and runtime efficiency
• C3SE offers computing power to run your simulations
• Versions used in this presentation:
• Python version: https://github.com/carlosnatalino/python-simple-anycast-
wdm-simulator
• Java version: https://github.com/carlosnatalino/java-anycast-cs-simulator/
• Presentation available at:
https://www.slideshare.net/CarlosNatalinoSilva/discreteevent-simulation-
best-practices-and-implementation-details-in-python-and-java