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Smart city can be considered as a process-intensive environment that needs to be as flexible as possible to support a continuously evolving scenario. In this paper we present an approach to support flexibility of Business Processes regulating the behavior of ICT systems deployed within a smart city. The approach permits to deal with large collections of process variants thanks to the integration of Business Process notations and Feature Model descriptions. The approach is applied to a smart mobility scenario with a specific focus on bike sharing systems.
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MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Modelling Process Intensive Scenariosfor the Smart City
R. Cognini, F. Corradini, A. Polini, B. Re
University of Camerino
IFIP EGOV 2014Trinity College, Dublin, Ireland
September, 3rd 2014
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Table of Contents
1 Motivations
2 A Smart City Scenario: The Bike Sharing System
3 bpFM - A Modeling Approach for BP variability
4 Conclusions and Future Work
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Smart City
The Smart city vision foster the integration of complexinfrastructures and systems to better organize resource usage andmake the city more citizen centric
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Smart Cities
Cities are different:
climate
terrain morphology
dimensions
inhabitants
. . .
Therefore:
Smart cities will be different even if they will have to facesimilar issues.
Differences and similarities will be reflected in the “installedsystems” and correspondingly in the supported businessprocesses that permit to “organize” and “use” the city
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Smart Cities
Cities are different:
climate
terrain morphology
dimensions
inhabitants
. . .
Therefore:
Smart cities will be different even if they will have to facesimilar issues.
Differences and similarities will be reflected in the “installedsystems” and correspondingly in the supported businessprocesses that permit to “organize” and “use” the city
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Organizing BP for the Smart City
Our objective was to investigate on tools and languages permittingto exploit commonalities still having the possibilities to derivedifferent version of the same system dipendently from the needs ofa specific smart city
Two main ingredients:
Business Process Modeling
Software Product Line and Feature Modeling
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Organizing BP for the Smart City
Our objective was to investigate on tools and languages permittingto exploit commonalities still having the possibilities to derivedifferent version of the same system dipendently from the needs ofa specific smart city
Two main ingredients:
Business Process Modeling
Software Product Line and Feature Modeling
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
BP modeling
A BP is the result of reflection and synthesis on different aspectsof an organization, and in order to better set up its activities.Particularly relevant for us are the functional, behavioral, andinformation views.
BPMN2 (OMG standard) is currently the most used notation tomodel BP. A simplified view:
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Software Product Line and Feature Modeling
Software Product Lines (SPL)
refer to methods, tools and
techniques for creating a collection
of similar software systems
Feature Model (FM) is a modeling
approach emerged in the context of
SPL in order to support the
development of a variety of products
from a common platform
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Bike Sharing System
The Bike Sharing System (BSS) is a bike rental solution thatenable citizens and tourists to move within a city using a bike. Theusers of a BSS tipically pick up a bike from one of the bike station(docking station) distributed in the city, and she can return it inany other bike station
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Bike Sharing System
The management and usage of the BSS subsumes the possibility ofactivating many different BPs. Service subscription, bikeusage/travel, bike redistribution, credit acquisition, . . .
The Bike Usage/Travel Business Process refers to the BP familypermitting to a user (citizen or tourist) to register and access aBSS to pick up a bike from a bike station, to use it to go around,and finally to return the bike to the same or a different bike station(for instance including or not activities to apply rewarding policies)
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The bpFM approach to variability modeling
The approach we propose mixes the characteristics and objectives of the twodifferent modeling context we introduced before.
To model BPs variability an extended version of FM has been introduced,named business process Feature Model (bpFM), in which the features representthe activities characterizing a process (functional view). Among the activitiesrelations are defined similarly to what is done in FODA.
A set of mapping rules from bpFM to BPMN 2.0 fragments has been defined
Successively according to a specific feature selection (configuration) a detailedBP skeleton can be automatically derived
It is also possible to add information concerning the input and output dataobject related to an activity (information view)
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
bpFM Constrains
Elements in the bpFM notation permits to specify relation amongactivities and if an activity has to be executed or not by a BPenactment
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Mapping to BPMN
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Mapping to BPMN
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Mapping to BPMN
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: The bpFM model
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: Mapping Example
The selection of an activity (feature) results in the generation ofthe correspondingly BP fragment
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: The BP skeleton
The mapping rules permits to derive a variant skeleton including allthe selected activities given the configuration, as well as thedefinition of some behavioral constraints. The inclusion of dataflow relations further constraint the behavioral relations in the BPskeleton
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: A BP Variant
The BP variant is finally obtained including all the behavioralconstraints
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Conclusions and future work
Variability needs to be more and more taken into account also in order toreduce costs. We presented an approach to model variability of BPpermitting to include in a single model many different variants of thesame BP. The approach permits to the modeler to focus on differentviews (functional, behavioral, . . . ) at different times
Adopting the approach it is possible to reduce the complexity ofmanaging many different variants of a BP and to share experiencesbetween different smart city initiatives. The initial experiments weconducted provided encouraging results.
There are many items in the future work list. Among the others:
continue experiments and validation
finalize the supporting tool chain
study the possible extension of the approach to considermulti-organizational BPs
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
EU financed projectModel-Based Social Learning for Public Admin. (Learn PAd)
http://www.learnpad.eu
Thank you!
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
MotivationsA Smart City Scenario: The Bike Sharing SystembpFM - A Modeling Approach for BP variability
Conclusions and Future Work
EU financed projectModel-Based Social Learning for Public Admin. (Learn PAd)
http://www.learnpad.eu
Thank you!
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City
