An Evolution-by-design Approach: Toward Multi-disciplinary Life-cycle Management of IoT in City Platform as a Service

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An Evolution-by-design Approach:
Toward Multi-disciplinary Life-cycle Management
of IoT in City Platform as a Service
ICTC2017, Jeju, Korea
Toshihiko Yamakami
IoT Business Unit, ACCESS
Toshihiko.Yamakami@access-company.com
2017/10
Toshihiko Yamakami (ACCESS Confidential)An Evolution-by-design Approach: Toward Multi-disciplinary Life-cycle Management of IoT2017/10 1 / 21

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Outline
Background
Related Work
Research Method
Model
Stage Model of Smart IoT (3rd stage: Evolution-by-Design)
Layer Model of Complexity of Smart IoT
3-Dimensional Model of Smart IoT for Evolution-by-Design
Examples of Dimensional Design
Examples of Space-Dimensional Support of Evolution
Examples of Time-Dimentional Support of Evolution
Discussion
Advantages of the Proposed Model
Limitations
Conclusion

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Background
Research Purpose
The aim of this research is to develop a licecycle management
framework of smart IoT in order to deal with the interactions of diverse
components of smart IoT systems in time and space dimensions.
Backgrounds
IoT consists of multi-disciplinary integration of hardware, software,
deployment, usability, operation, maintenance, adoption and
ecosystems.
Drawing a beautiful drawing of the final ideal future does not guarantee
the healthy growth of a smart city. A city is an ecosystem that deals
with security, lives, communities, desires, culture, businesses, plans,
coordination, enforcement, and interactions.
A framework to deal with “living things” to evolve is necessary.

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Related Studies
a) IoT integration
[daSilva:2016] automating deployment of heterogeneous IoT devices
[Joy16] integration of GPS-enabled IoT devices and a privacy protection
module
[Rosenkranz15] continuous integration of open IoT software and networks
and embedded software
b) high-level management of smart cities
[Zomer15] integration of three world views of different stakeholders of a
smart city
[Cohen14] policy and trust issues in Smart Cities IT infrastructure
[Amaba14] integration of multi-disciplinary skills to truly develop Smart Cities
c) life-cycle management of IoT systems
[Neto16] authentication and access control mechanism throughout IoT
life-cycle
[Moore16] three-tiered DevOps model for high-level management of
city-scale IoT integration
The originality of this paper lies in its identification of a dimensional
framework for life-cycle management of smart IoT systems.

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Research Method
analyze interactions of different components of IoT systems,
analyze the life-cycle management of smart IoT systems,
present a model to deal with the long-term evolution management of
smart IoT systems
present design based on the proposed model to deal with
time-dimensional and space-dimensional evolution of smart IoT
systems.

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Overview of CPaaS.io
Smart City Innovation is the goal of the CPaaS.io joint R&D project
between Europe and Japan starting from 2016.
To achieve this, the CPaaS.io platform combines the capabilities of
the Internet of Things (IoT), big data analytics and cloud service
provisioning with Open Government Data and Linked Data
approaches.
CPaaS.io hosts multiple projects in different cities in Europe and
Japan, e.g. Utrecht, Amsterdam, Tokyo, Sapporo, and Yokosuka.
URL: https://cpaas.bfh.ch/ CPaaS.io – City Platform as a Service

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Stage Model of Smart IoT
Technology
-centered stage
- People
-centered stage
- Evolution
by-design stage

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Description and Challenges for Each Stage
Stage Description Challenges
Technology-
centered
Technology-centered ap-
proach to focus technol-
ogy components to deal
with issues.
Social factors like trust, adoption, community
support, education and policies impact contri-
bution of IoT systems. For inclusion of enter-
prise stakeholders, business models and ecosys-
tems are also critical. Long-term sustainable
operation and maintenance also impact the
success in a long span of time.
People-
centered
Introduction and accep-
tance are managed by
people-centered approach
such as participatory de-
sign. Education and com-
munity support also con-
tribute the long-life of IoT
systems.
Complexity of today’s IoT is overwhelming to
many existing institution in a technological, op-
erational, and ecosystem-level. Also, long-term
evolution of large-scale IoT systems is beyond
the grasp of any ordinary people.
Evolution by
design
Evolution is captured by-
design to enhance feed-
back loop of multiple
stakeholders and scenes.
By-design components depend on contexts and
are no silver bullet. Also, long-term evolution
of IoT systems is largely unexplored field and
difficult to be empowered by any practical ex-
isting frameworks.

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Layer Model of Complexity of Smart IoT
Hardware Software Integration
Deployment Operation Maintenance
Usability Introduction Acceptance
Business Models Eco-Systems Value Systems
Development
Realization
User Behavior
Sustainability

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Examples of Intra-layer Interaction
Components Interactions
Hardware,
Software
Hardware impacts detect-ability, availability, reliability, and per-
formance of software. Software impacts battery life, heat, and
duration of hardware.
Hardware,
Integration
Hardware impacts every aspects of integration. Integration im-
pacts reliability, inter-workability, security and maintainability of
hardware.
Software, In-
tegration
Software impacts every aspect of integration. Integration impacts
functionality, performance, security, availability, reliability, and ex-
tensibility of software.
Deployment,
Operation
Deployment impacts configurability, reliability, security of opera-
tion. Operation impacts requirements of deployment.
Deployment,
Maintenance
Deployment impacts maintainability and time to repair. Mainte-
nance impacts requirements of deployment.
Usability, In-
troduction
Usability is one of key factors for introduction. Introduction sets
the early stage expectation of usability.
Introduction,
Acceptance
Usability is the entry point of acceptance and determines the initial
attitude of acceptance. Acceptance impacts introduction of further
features.
Business Business models impact frameworks of potential eco-systems.Toshihiko Yamakami (ACCESS Confidential)An Evolution-by-design Approach: Toward Multi-disciplinary Life-cycle Management of IoT2017/10 10 / 21

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Examples of Inter-layer Interactions of Smart IoT
Layers Interaction
Development, Real-
ization
Aspects of development impacts requirements of realization. Con-
texts and processes of realization provide requirements of develop-
ment.
Development, Sus-
tainability
Quality of development influences sustainability. Sustainability im-
pacts supports of continuing development.
Development, User
behavior
Quality of development impacts every component of user behavior.
User behavior provides requirements of development.
User behavior, Sus-
tainability
User behavior determines sustainability. Sustainability influences ad-
ditional supports of development and realization, which in turn im-
pact user behavior.
Realization, Sustain-
ability
Quality of realization impacts sustainability. Sustainability influences
continuing supports of continuing realization.
Realization, User be-
havior
Quality of realization impacts every component of user behavior.
User behavior provides requirements of realization.

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3-Dimensional Model of Smart IoT for Evolution-by-Design
-
6
+
Implementation,
integration, and
Operation of
each IoT system
Time-dimensional support
for IoT Life-cycle Management
Space-dimensional support
for cross-boundary integration,
operation, and learning

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Space-Dimensional (Cross-Boundary) Evolution Model
Cross-boundary
Linkage
- Learning - Integration

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Example of Space-dimensional Support of Evolution
[Space-dimensional cross-border coordination of Smart IoT:
various device and business model cross-border integration]
[People and Things]
- People and Sensor(sensor-linked chat)
- On-demand learning(context-sensed)
- Robot-enterprise system integration
- Context-aware workflow (BLE)
[Cross border Linkage]
- Monitoring, reporting, action execution
firmware updates(OMA LwM2M)
- Bot coordination
- Embedded AI (minimum AI engine)
[Connected assurance]
- Device Coordination (LwM2M)
- Edge Computing (edge engine)
- Service Linkage (IoT platform)
- LPWA (RoLaWAN Server)
[Business Model Linkage]
- Regional business platform
- Sharing economy support with
location and context
- IoT new business (notification beacon)

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3-phase Loop Model
Design - Deployment - Feedback
6

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Example of Time-dimensional Support of Evolution
[Smart IoT Time-dimensional support:
Supporting heterogeneous organizations and processes in an add-on-based manner
[People: confirmation,
communication, safety]
- stamp communication (chat))
- entry/exit monitoring (BLE)
- outdoor vital health monitoring
- barcode login (mobility platform)
[Things: management, update,
locating]
- monitoring, reporting, activation
firmware update(LwM2M)
- location confirmation(BLE)
- video monitoring at edge (edge engine)
[Information: sharing,
display, matching]
- information sharing(sensor-linked chat)
- context-aware digital signage
- on-demand learning
(browser-based education)
- notification beacon
[Process: management,
recording]
- transaction logging (easy-to-use logging)
- sharing of facilities, vehicles,
heavy equipment (matching platform)
- vehicle route management
(mobility platform)

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Comparison of Approaches
Approach Pros Cons
Top-down
approach
It is concept-driven and fits well
when the given framework of the
design is aligned to the real world
in a long-term manner.
It is fragile for long-term evo-
lution of real-world IoT. It does
not work well when the intuitive
design does not deal with the
whole complexity.
Bottom-up
approach
It fits well as far as each compo-
nent fits the real-world reality. It
can deal with the reality when each
instance fits the targeted niche.
It does not work well when
each part of instance does not
deal with interactions of differ-
ent components well.
Abstraction
approach
It fits well when abstraction
works well in a hardware-agnostic,
network-agnostic, and data-
agnostic manner.
It does not work well when ab-
straction requires much over-
head in the deployment of
niche-fit IoT.
Evolution-
by-design
approach
It fits well when the dynamic as-
pects of cross-boundary and long-
term evolution is covered by the el-
ements of evolution support.
It does not work well when the
cross-boundary and long-term
evolution factors does not con-
tribute the holistic characteris-
tics of smart IoT.

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Advantages of the Proposed Approach
The proposed layered view model of complexity of IoT presents a
stepping stone to awareness of complexity. It can be used for a
checklist of component and interactions in order to prepare to deal
with complexity.
The proposed concept of evolution-by-design provides a methodology
to empower dynamic evolution of smart IoT systems with awareness of
additional dimensions of life-cycle support: a time-dimensional and a
space-dimensional support.
The proposed life-cycle management model of IoT provides a
foundation to leverage the open loop of dynamic evolution of IoT in a
sustainable large-scale IoT ecosystem such as a smart city.
Design examples described in this paper provides a guidance of
surrounding support for IoT life-cycle management when multiple
heterogeneous stakeholders are involved which is a common case of
smart cities.

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Limitations
This research is qualitative and exploratory. Detailed study of intra-layer and
inter-layer interactions in the real-world case studies are not covered in this
paper. Quantitative analysis of intra-layer and inter-layer interactions
remains for future study.
Detailed impact analysis of evolution-by-design is not performed in this
paper. Quantitative measures to evaluate influence of an evolution-by-design
approach are not studied in this paper.
Real deployment of an smart-IoT model-based design and its impacts are not
investigated in this paper. Comparison of the proposed method based on the
real-world cases is not performed in this paper.
Long-term evaluation of the proposed method requires investigation of
multi-faceted and multi-disciplinary analysis. Collecting hard-evidence of
feedback and cross-boundary aspects of smart IoT remain for for future
study.
Social, Cross-cultural, cross-regional, and infra-structure-dependent factors
are not examined in this paper. Inter-dimensional factors in the proposed
smart IoT model are not a part of this research.

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Conclusion
Combined power of embedded computing, sensors, wireless communications,
clouds, data mining, and artificial intelligence is starting to realize total
digital transformation of real world scenes.
Hardware, software, deployment, operation, maintenance, adoption, and
ecosystems require time-consuming efforts to deal with the real-world by the
unprecedented complexity.
In this paper, the author discusses the complexity of smart IoT and presents
a layered view model of IoT complexity. Then, the author presents
importance of life-cycle support of IoT. From this perspective, the author
proposes a 3-dimensional model of smart IoT support including
evolution-by-design support. Finally, the author presents time-dimensional
and space-dimensional support of IoT evolution.
The proposed method is a stepping stone toward the shift of instance
implementation to whole process of evolution of smart IoT.

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Thank You for Your Attention!
Questions?

An Evolution-by-design Approach: Toward Multi-disciplinary Life-cycle Management of IoT in City Platform as a Service

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