Disclaimer: this is a rehearsal for a conference and has not been elaborated nor was meant to be published, the audio and video are rough and may contain imperfections, there is no pointer and audio/video may be out of synch. I decided to publish these videos afterwards as further material to complement the published papers.

1. Tuning energy consumption strategies in the railway
domain: a model-based approach
Davide Basile Felicita Di Giandomenico Stefania Gnesi
Istituto di Scienza e Tecnologia dell’Informazione “A. Faedo”,
Consiglio Nazionale delle Ricerche, ISTI-CNR, Pisa, Italy
ISOLA 2016, 10/2016
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

2. Overline of the presentation
1 Motivations and Objectives
2 The System Under Analysis
3 SAN Models
4 Results of the Analysis
5 Conclusion
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

3. Section 1
Motivations and Objectives
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

4. Motivations and Objectives
Energy management: relevant political, societal and technological
concern;
Reducing Energy consumption ⇒ Goal of IT systems;
Benefits:
costs,
environment (reputation, avoid penalties),
risks (price fluctuations, energy shortages);
Critical applications: Dependability vs Energy Consumption;
Case study: rail road switch heating system;
Stochastic-model based analysis to design and evaluate.
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

5. Stochastic Model-Based Analysis
Design and evaluation of systems;
abstraction level;
life-cycle of software;
Stochastic Activity Networks:
places,activities,I/O gates;
instantaneous/timed activity
(stochastic distribution of time),
probabilistic cases;
policies of activation/reactivation of
activities;
C++ code.
M¨obius: a modular tool, analytical and
simulative solvers;
for evaluating energy consumption and
reliability;
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

6. Stochastic Model-Based Analysis
Design and evaluation of systems;
abstraction level;
life-cycle of software;
Stochastic Activity Networks:
places,activities,I/O gates;
instantaneous/timed activity
(stochastic distribution of time),
probabilistic cases;
policies of activation/reactivation of
activities;
C++ code.
M¨obius: a modular tool, analytical and
simulative solvers;
for evaluating energy consumption and
reliability;
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

7. Stochastic Model-Based Analysis
Design and evaluation of systems;
abstraction level;
life-cycle of software;
Stochastic Activity Networks:
places,activities,I/O gates;
instantaneous/timed activity
(stochastic distribution of time),
probabilistic cases;
policies of activation/reactivation of
activities;
C++ code.
M¨obius: a modular tool, analytical and
simulative solvers;
for evaluating energy consumption and
reliability;
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

8. Section 2
The System Under Analysis
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

9. Rail road switch heating system
Rail road switches: critical system;
Heating system: tubular flat heaters, induction heating;
Cyber-Physical System: sensors for the temperatures;
physical part: weather (statistic data), heat exchange (ODE), layout of
station
Policies of Energy Consumption: Energy vs Reliability;
Modular, parametric and extensible approach.
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

10. Energy-saving Policies
Dynamic Power Management, on/off policy based on two
thresholds:
warning threshold Twa: guarantees reliability;
working threshold Two: guarantees energy saving;
energy supply NHmax ;
FIFO Priorities;
Coordinator to manage NHmax and priorities.
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

11. Energy-saving Policies
Dynamic Power Management, on/off policy based on two
thresholds:
warning threshold Twa: guarantees reliability;
working threshold Two: guarantees energy saving;
energy supply NHmax ;
FIFO Priorities;
Coordinator to manage NHmax and priorities.
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

12. Energy-saving Policies
Dynamic Power Management, on/off policy based on two
thresholds:
warning threshold Twa: guarantees reliability;
working threshold Two: guarantees energy saving;
energy supply NHmax ;
FIFO Priorities;
Coordinator to manage NHmax and priorities.
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

13. Energy-saving Policies
Dynamic Power Management, on/off policy based on two
thresholds:
warning threshold Twa: guarantees reliability;
working threshold Two: guarantees energy saving;
energy supply NHmax ;
FIFO Priorities;
Coordinator to manage NHmax and priorities.
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

14. Static vs Flexible Policy
Twa Twah
Twam
Twal
Twam
Twah
Static Flexible
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

15. Section 3
SAN Models
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

16. Composed Model
interactions through shared places
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

17. Interactions 1
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

18. Interactions 2
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

19. Interactions 3
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

20. Interactions 4
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

21. RailRoadSwitchHeater SAN
init
clock
heater
mc ∂T
∂t = −uA(T − Tenv ) + ˙Q
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

22. Section 4
Results of the Analysis
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

23. Results: Measures of Interest
CE(t,l): the energy consumed by a generic heater in the interval
[t, t + l] (24 hours);
PFAIL(t,l): the probability that a switch fails at time t + l, given
that at time t is not failed;
Parameters:
thresholds ∈ [6◦
C, 10◦
C], NHmax = 50%;
41 switches: 23 high, 6 medium, 12 low priority
Flexible vs Static policy, two different strategies:
fixed Two−Twa= 1 ◦
C;
fixed Two;
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

24. Results: Two − Twa = 1◦
C, optimal Twa
(7.50;6.75;6.75)
(7.50;7.00;7.00)
(6.00;7.00;7.25)
(7.50;7.00;7.25)
(7.00;7.25;7.00)
(7.50;7.25;7.00)
(6.25;7.25;7.25)
(6.00;7.50;7.00)
(6.50;7.50;7.00)
(6.50;7.50;7.50)
(6.75;7.50;7.50)
(7.50;7.75;7.50)
(7.75;7.75;8.00)
(8.00;7.75;8.00)
(6.25;8.00;7.00)
(6.50;8.00;7.00)
(6.75;8.00;7.00)
(7.50;8.00;7.00)
(6.00;8.00;7.25)
(6.25;8.00;7.75)
(6.00;8.00;8.00)
(6.25;8.00;8.00)
6
7
0.5
1
· 10−3
6.67·10−5
5·10−5
8.33·10−5
6.67·10−5
6.67·10−5
6.67·10−5
5·10−5
8.33·10−5
6.67·10−5
6.67·10−5
8.33·10−5
6.67·10−5
8.33·10−5
5·10−5
8.33·10−5
8.33·10−5
6.67·10−5
8.33·10−5
6.67·10−5
1.67·10−5
6.67·10−5
3.33·10−5
1.3·10−3
1.67·10−5
Twa,mp
PFAIL(t,l)
6
(6.25;6.75;7.00)
(6.50;6.75;7.00)
(6.75;6.75;7.00)
(7.00;6.75;7.00)
7
(6.00;7.75;7.00)
(6.25;7.75;7.00)
(6.50;7.75;7.00)
(6.75;7.75;7.00)
(7.00;7.75;7.00)
(7.25;7.75;7.00)
(6.75;8.00;6.75)
(6.00;8.00;7.00)
(6.25;8.00;7.00)
(6.50;8.00;7.00)
(6.75;8.00;7.00)
(7.00;8.00;7.00)
(7.25;8.00;7.00)
(8.00;8.00;7.00)
8
2 · 10−2
4 · 10−2
6 · 10−2
8 · 10−2
0.1
4.83·10−2
9.73·10−3
9.92·10−3
9.9·10−3
9.92·10−3
1.64·10−2
7.95·10−3
6.57·10−3
6.56·10−3
7.43·10−3
7.12·10−3
7.68·10−3
9.92·10−3
5.21·10−3
4.63·10−3
5.21·10−3
5.15·10−3
4.9·10−3
5.37·10−3
7.35·10−3
0.1
Twa,lp
(7.50;6.75;6.75)
(7.50;7.00;7.00)
(6.00;7.00;7.25)
(7.50;7.00;7.25)
(7.00;7.25;7.00)
(7.50;7.25;7.00)
(6.25;7.25;7.25)
(6.00;7.50;7.00)
(6.50;7.50;7.00)
(6.50;7.50;7.50)
(6.75;7.50;7.50)
(7.50;7.75;7.50)
(7.75;7.75;8.00)
(8.00;7.75;8.00)
(6.25;8.00;7.00)
(6.50;8.00;7.00)
(6.75;8.00;7.00)
(7.50;8.00;7.00)
(6.00;8.00;7.25)
(6.25;8.00;7.75)
(6.00;8.00;8.00)
(6.25;8.00;8.00)
6
7
10
10.5
11
10.54
10.69
10.37
10.69
10.51
10.69
10.51
10.51
10.51
10.57
10.58
10.74
10.96
11.16
10.7
10.69
10.69
10.69
10.7
10.78
10.82
10.81
9.99
10.51
Twa,mp
CE(t,l)
6
(6.25;6.75;7.00)
(6.50;6.75;7.00)
(6.75;6.75;7.00)
(7.00;6.75;7.00)
7
(6.00;7.75;7.00)
(6.25;7.75;7.00)
(6.50;7.75;7.00)
(6.75;7.75;7.00)
(7.00;7.75;7.00)
(7.25;7.75;7.00)
(6.75;8.00;6.75)
(6.00;8.00;7.00)
(6.25;8.00;7.00)
(6.50;8.00;7.00)
(6.75;8.00;7.00)
(7.00;8.00;7.00)
(7.25;8.00;7.00)
(8.00;8.00;7.00)
8
10
10.5
9.58
10.13
10.17
10.21
10.24
10.25
10.52
10.54
10.54
10.53
10.53
10.53
10.49
10.58
10.59
10.59
10.58
10.58
10.59
10.64
9.99
Twa,lp
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

25. Results: Two − Twa = 1◦
C, impact of Twal
7
(10;7;7)
(7;7;10)
(7;10;7)
0
0.2
0.4
0
2.48·10−4
0
0
1.67·10−5
6.38·10−3
2.87·10−3
1.92·10−2
1.64·10−2
3.57·10−2
0.56
0.18
Twa
PFAIL(t,l)
high priority
medium priority
low priority
7
(10;7;7)
(7;7;10)
(7;10;7)
8
10
10.56
11.59
11.34
11.31
10.51
10.96
10.87
10.66
10.25
10.28
6.49
8.98
Twa
CE(t,l)
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

26. Results: Two − Twa = 1◦
C, “bad” thresholds
6
(7;6;7)
(8;6;8)
(9;6;9)
(10;6;10)
0
0.2
0.4
0.6
0
0
0
3.96·10−4
2.69·10−3
1.3·10−3
2.67·10−4
1.38·10−2
3.92·10−2
0.21
4.83·10−2
6.76·10−2
0.23
0.47
0.6
Twa
PFAIL(t,l)
high priority
medium priority
low priority
6
(7;6;7)
(8;6;8)
(9;6;9)
(10;6;10)
8
10
10.19
10.51
10.97
11.49
11.88
9.99
10.45
10.5
10.68
9.54
9.58
9.58
8.66
7.19
6.78
Twa
CE(t,l)
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

27. Results: Low priority heaters, fixed Two
(6.75;6.75;6.75)
(7.25;8.00;7.00)
9
8.75
8.5
8.25
8
0.1
0.2
Twa
Two
PFAIL(t,l)
0.1
0.2
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

28. Section 5
Conclusion
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

29. Conclusion
Model-based analysis for a rail road switch heating system;
SAN and M¨obius tool to evaluate energy consumption and probability
of failure at varying of temperature thresholds and available energy;
Physical model for calculating the temperature of the rail road track;
Comparisons between flexible and static thresholds;
Results: flexible thresholds are better than static ones;
Future works: different layouts (i.e. priorities) of the station
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016

30. References
Basile, D., Chiaradonna, S., Di Giandomenico, F., Gnesi, S.: A stochastic
model-based approach to analyse reliable energy-saving rail road switch
heating systems. JRTPM (2016),
Basile, D., Chiaradonna, S., Di Giandomenico, F., Gnesi, S., Mazzanti, F.:
Stochastic model-based analysis of energy consumption in a rail road switch
heating system. SERENE 2015. LNCS 9274
Basile, D., Di Giandomenico, F., Gnesi, S.: Tuning energy consumption
strategies in the railway domain: a model-based approach. In: ISOLA 2016
Basile, D., Di Giandomenico, F., Gnesi, S.: ”Energy Consumption
Assessment of Reliable Systems through Stochastic Model Based Analysis”
in Green IT Engineering: Concepts, Models, Complex Systems Architectures,
Volume 1, Springer Book series Studies in Systems, Decision and Control
Basile D, Di Giandomenico F., Gnesi S., Supporting the Design of Intelligent
Railway Stations. I-CiTies 2015 -CINI Annual Conference on ICT for Smart
Cities &Communities 2015
D.B. et al. (ISTI CNR) Stochastic Model Based Analysis ISOLA 2016 25 / 25