The variability scale in large-scale Cyber-Physical Systems (CPSs) is high and complex due to the voluminousness, dynamicity and diversity of available computing resources (people, things and software services), domain-specific processes, domain-specific elements (stakeholders, assets and contracts), and their relationships. This requires us to go beyond current variability modeling and management techniques which neglect the complexity and the diversity of relevant stakeholders, data and assets, and thus cannot cope with intelligent business and analytics requirements in dynamic environments, such as smart city management. In this paper, we present a comprehensive analysis for understanding the multi-perspective variability in processes atop people, data and things in CPSs, particularly, for the sustainability governance of Smart Green Buildings (SGBs). We examine domain-specific processes and domain-specific elements and their relationships to derive a multiple perspective variability management for SGBs. On the basis of this, we conceptualize a novel model for the multi-perspective process variability representation.

1. Multi-perspective Process Variability:
A Case for Smart Green Buildings
Aitor Murguzur 
Hong-Linh Truong ✪ Schahram Dustdar ✪
Software Production Area, IK4-Ikerlan Research Center✪ Distributed Systems Group, Vienna University of Technology
amurguzur@ikerlan.es | truong@dsg.tuwien.ac.at | dustdar@dsg.tuwien.ac.at
The 6th IEEE International Conference on Service-oriented Computing and Applications
KAUAI HAWAII, USA | DEC 17, 2013

2. Outline
1 Motivation
2 Analyzing multi-perspective process
variability
3 Conceptualizing multi-perspective
process variability
4 Prototype
5 Next steps
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
2

3. Motivation
smart cities and smart green buildings
(SGBs)
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
@image: courtesy of Pacific Controls)

4. Governance life-cycle
motivation
DESIGNERS, OWNERS, PROVIDERS
Optimization
Optimization plans.
Correction actions.
DESIGNERS,
OWNERS,
PROVIDERS,
OPERATORS,
ANALYSTS,
COMMUNITY,
TENANTS
INSTALLATION AND
COMMISSIONING
SURVEYING
Analytics
Prediction.
Assessments.
Auditing.
Policy & Design
Standards and business
goals.
KPIs.
Business processes and
rules.
System architecture.
CONGURATION
OPERATION
OPERATORS
Implementation
Device interaction and
monitoring.
Real-time event catching.
Data collection.
ANALYSTS, COMMUNITY
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
4

5. SGB process variability
motivation
Installation and
Commissioning processes
Configuration processes
Operation processes
Surveying processes
Process variability
People
Stakeholders and
roles.
Operation contracts.
Data
Static context data.
Dynamic context data.
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
Things
Monitored assets.
Building types.
5

6. Managing commonalties/individualities
motivation
Multiple
perspectives
of variability
SGBs
solutions
STAKEHOLDERS
SGB 1
SGB 2
MONITORED
ASSETS
SGB 3
OPERATION
CONTRACTS
SGB 4
SGB 5
BUILDING
TYPES
...
Processes and
instances
...
-Installation and
commissioning
-Operation
-Configuration
-Surveying
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
6

7. MOTIVATING EXAMPLE
Approach
Multiple
perspectives
of variability
SGBs
solutions
STAKEHOLDERS
SGB Solution
Cloud Service
Platform
MONITORED
ASSETS
OPERATION
CONTRACTS
BUILDING
TYPES
SGB 1
Processes and
instances
-Installation and
commissioning
-Operation
-Configuration
-Surveying
A number of buildings
A plethora of related process variants
(e.g. energy efficiency process, energy consumption, chiller optimization, etc.)
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
7

8. The paper‘s focus
• Understanding multiple perspectives in process
variability
• Conceptualize and modeling multi-perspective
process variability
• Provisioning SGB solutions under the cloud
– Build solutions for operation processes based
multi-perspective process variability
– Packaging and providing a service model for SGB
solutions of operation processes
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
8

9. Multi-perspective in process variability
Stakeholders and interactions in SGBs
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
9

10. Multi-perspective in process variability
Operation processes
BUILDING HEALTH STATUS
TENANT BILLING (OP7)
MAINTENANCE (OP1)
energy efficiency (OP8)
individual equipment maintenance (OP2)
demand monitoring and prediction (OP9)
electricity system maintenance (OP3)
DATA ANALYSIS (OP10)
mechanical system maintenance (OP4)
Compliance with Regulation (OP11)
platform maintenance (OP5)
energy consumption (OP6)
user comfort monitoring (OP12)
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
10

11. An energy consumption process
Process variability related to building facilities
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
11

12. An energy consumption process
Process variability related to monitored assets
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
12

13. An energy consumption process
Process variability related to stakeholders
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
13

14. Concepts
Multi-perspective in process variability
•
•
multi-perspective is related to multiple stakeholders’ configurations
support (multi-tenancy), providing them more accurate views
separate variability dimensions (e.g. data variability)
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
14

15. Modeling
Multi-perspective in process variability
• using a single variability model: a single feature
model.
• using multiple variability models: one feature model for
each perspective.
• make use of the Base-Variation-Resolution approach
- Base model - representing commonalities.
- Variation model - representing individualities.
- Resolution model - representing process variant
configurations.
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
15

16. Sample
Multi-perspective in process variability
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
16

17. Prototype: lateva toolkit
Staged variability resolution and execution
lateva methodology: a fragment-based re-use approach, separating model
commonality, variability and possible configurations into separate models.
Base Model: the Greatest Common
Denominator (GCD) of all related
process variants.
Fragment: a single variant realization
option for each variation point within a
particular base model.
LateVa is an Activiti (http://activiti.org) extension for representing
base models and fragments variability using BPMN2
Base model and fragments specification using
BPMN2
Murguzur, A., Sagardui, G., Intxausti, K., Trujillo, S.: Process Variability through Automated Late Selection of
Fragments. In: VarIS workshop, collocated at CAiSE. (2013)
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
17

18. Prototype: sample
Lateva toolkit: Modeling multi-perspective process
variability
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
18

19. Next steps
configuration and execution: automated
resolution of multi-perspective process
variability.
empirical evaluation: tests on industrial
case studies.
solution package: cloud-based SGB
solutions provisioning.
SOCA 2013, Kauai, Hawaii, 17 Dec 2013
19

20. thank you
amurguzur@ikerlan.es | truong@dsg.tuwien.ac.at | dustdar@dsg.tuwien.ac.at