1. IoT and Cloud Convergence:
Opportunities and Challenges
A. Rahim Biswas Create-Net, Italy

2. Outline
 IoT and Cloud vision and requirements
 Convergence approach’s
 Example of existing platform
 Emerging challenges of IoT/Cloud

3. "Cloud computing a new business model and
management (e.g. data and device) paradigm of
Internet of thing"
Statements
”IoT is to enlarge the opportunities of cloud
service provisioning "

4.  IoT is the vision of future connected physical and
virtual world, several billions of heterogeneous
devices/objects and big data, to provide smart
and personalize services to users
 Connectivity, convergence and intelligent
everywhere
What is IoT?

5.  A real-time online platform that
 Dynamically management IoT data/objects and
 Provide connectivity of the diverse
heterogeneous objects, considering the
interoperability issues
 Deriving the value (useful information and
knowledge) from this connection and large
volume of IoT data
Major IoT platform requirements

6. IoT Enablers
Cloud

7.  Ubiquitous accessibility and connectivity,
facilitation of maximum accessibility as well as
connectivity of the diverse heterogeneous
objects/services and various volumes of users
including mobility
 Dynamic management/orchestration of users,
billions of devices as well as massive amount of
data produced by those connected devices
IoT platform functionalities (1/2)

8.  Maximum resources utilization, enabling of
sharing of IoT resources (objects,
applications, platforms)
 Personalization of users and services,
providing services based on users preference
and requirements including real-world
context
IoT platform functionalities (2/2)

9.  Dynamic resources sharing platform
 Offers scalable, elasticity resources and
services management
 Location independent can be access from any
where
 Reliable and easy access of the services
 Large amount of computing and storage
resources
 It is also more homogeneous
What Cloud offers?

10.  For IoT to provide cloud computing
functionalities, to support on realization of
IoT vision
 For Cloud, IoT to provide huge opportunities
for cloud services
Convergence of IoT and Cloud

11.  Cloud-centric IoT (Bring IoT functionalities in
Cloud)
 IoT-Centric Cloud (Bring Cloud functionalities
in IoT
Convergence approach’s

12.  Bring IoT data in the cloud
 Processing and computing the data and
deploy management tools in cloud
 This approach this good if service are
provided among objects located in multiple
location
 Giving several example (market platform,
project platform..)
Cloud-centric IoT

13.  ThingWorx IoT software Platform
 Providing IoT service for SMEs, industries, business chain
 It provides complete application, run-time and intelligent environment
ThingWorx IoT Software Platfrom

14.  Carriots platform as a service design for IoT and M2M
application
Carriots Cloud platform

15. Axeda IoT Cloud Services

16. SensorCloud platform
 MicroStrain’s SensorCloud™ is a unique sensor data storage,
visualization and remote management platform that leverages
powerful cloud computing technologies to provide excellent
data scalability, rapid visualization, and user programmable
analysis.

17. Cloud-centric IoT platform
IoT Cloud Platform
hosting databases applicationspartners SI
All devicesOur managed
devices
your devices
Simple, scalable, robust, resilient, trustful & secure17
FBConsulting,OneM2Mpresentation;BasedonETSISmartCityWS
June2013presentationM.Arndt,ORANGE.
Cognitive
capability

18.  IoT infrastructure will provide the opportunities
to take services, workloads, applications and
large amounts of data and deliver it all to the
edge of the network.
 Processing and storage of data close to
users/near to sources
 To distribute data to move it closer to the end-users to
eliminate latency, numerous hop, and support mobile
computing and data streaming
 Creating dense geographical distribution
IoT- Centric Cloud (1/2)

19.  This approach are useful when service is
provisioned from the data coming from same
location
 Supporting end-users security
 Data process and service execute locally
(distributed cloud processing, sub-work flow,
data aggregation locally)
IoT- Centric Cloud (2/2)

20. IoT-Centric cloud computing

21.  Real-time data processing and service provisioning
 “Big data” storage and processing for real-time services
 un-structure and semi-structure data coming from distributed
sources and requirements to provide real-time/near real-time
services
 More dynamic configuration/ resources
management/orchestration/automated provisioning of
resources from/to IoT
 Considering performance targets/constraints
 Offloading from clients/hosts to cloud
 At design and run time
 Including mobile users/apps
 Dynamic metering when IoT devices are shared
Emerging IoT-Cloud challenges (1/3)

22.  More distributed processing and storage of the massive data
as well as cloud functionalities
 Decentralized (and infrastructure-less) clouds
 Processing capabilities and data positioned closer to users
 Migration of servers to follow mobile users
 Virtualization of IoT devices: Access to advanced
resources/specialized hardware, including GPUs, sensors, etc.
 Emerging business model: Data-incentive cloud-based
applications
 Considering data migration issues and avoiding lock-in
Emerging IoT-Cloud challenges (2/3)

23.  Portability of the services
 Users experience creation and enablement
 Interoperability: Interoperability between cloud/IoT services
and infrastructure
 Accountability- Services and data hosted and executed
across borders
 Enabling reliable and real-time communication from objects
to applications and vice-versa;
Emerging IoT-Cloud Challenges (3/3)

24. iCore Project IoT Framework

25. Thank you very much
Questions
abdur.rahim@create-net.org