IoT and Cloud Convergence:
Opportunities and Challenges
A. Rahim Biswas Create-Net, Italy
Outline
 IoT and Cloud vision and requirements
 Convergence approach’s
 Example of existing platform
 Emerging challen...
"Cloud computing a new business model and
management (e.g. data and device) paradigm of
Internet of thing"
Statements
”IoT...
 IoT is the vision of future connected physical and
virtual world, several billions of heterogeneous
devices/objects and ...
 A real-time online platform that
 Dynamically management IoT data/objects and
 Provide connectivity of the diverse
het...
IoT Enablers
Cloud
 Ubiquitous accessibility and connectivity,
facilitation of maximum accessibility as well as
connectivity of the diverse ...
 Maximum resources utilization, enabling of
sharing of IoT resources (objects,
applications, platforms)
 Personalization...
 Dynamic resources sharing platform
 Offers scalable, elasticity resources and
services management
 Location independen...
 For IoT to provide cloud computing
functionalities, to support on realization of
IoT vision
 For Cloud, IoT to provide ...
 Cloud-centric IoT (Bring IoT functionalities in
Cloud)
 IoT-Centric Cloud (Bring Cloud functionalities
in IoT
Convergen...
 Bring IoT data in the cloud
 Processing and computing the data and
deploy management tools in cloud
 This approach thi...
 ThingWorx IoT software Platform
 Providing IoT service for SMEs, industries, business chain
 It provides complete appl...
 Carriots platform as a service design for IoT and M2M
application
Carriots Cloud platform
Axeda IoT Cloud Services
SensorCloud platform
 MicroStrain’s SensorCloud™ is a unique sensor data storage,
visualization and remote management pla...
Cloud-centric IoT platform
IoT Cloud Platform
hosting databases applicationspartners SI
All devicesOur managed
devices
you...
 IoT infrastructure will provide the opportunities
to take services, workloads, applications and
large amounts of data an...
 This approach are useful when service is
provisioned from the data coming from same
location
 Supporting end-users secu...
IoT-Centric cloud computing
 Real-time data processing and service provisioning
 “Big data” storage and processing for real-time services
 un-struc...
 More distributed processing and storage of the massive data
as well as cloud functionalities
 Decentralized (and infras...
 Portability of the services
 Users experience creation and enablement
 Interoperability: Interoperability between clou...
iCore Project IoT Framework
Thank you very much
Questions
abdur.rahim@create-net.org
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Internet of thing (IoT and cloud convergence opportunitis and challenges

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  • It is about to drive the relation between the objects and thing which did not explore


    The outline of the presentation is
    To show the internet of thing is about richer connection
    Connection to one objects are growing and growing….
    As like as economical message transition and connection boster the economy
    To compare the how this connect is growing …
    To assess the value of connection …
    Understand and robustness of each of the connection…
    It is about big data….
    These data need to process…. And need powere…
    Concept of local cloudl and global cloud
  • To provide services based on the uses requirements and users centric, IoT infrastructure is a BIG cloud of ubiquitous devices and objects, in where objects/devices are connected to provide user centric application and services.
    These devices are heterogeneous in nature and are location specific.
    The IoT deployed for certain purpose, difficult to re-use and is resources constraint and costly to deployed.

  • Ubiquitous accessibility (i.e., more business opportunities)
    Facilitation of maximal accessibility of objects/services through commonly agreed APIs and standards;
    Scalable, reliable dynamic management of massive amounts of data ("big data") produced by a huge number of diverse IoT connected devices
    Reliability (e.g., for handing context/policy changes and accomplishing trust from the parts of the users)
    Scalability (e.g., as various volumes of users, resources and data may be involved in service provision)
  • Ubiquitous accessibility (i.e., more business opportunities)
    Facilitation of maximal accessibility of objects/services through commonly agreed APIs and standards;
    Scalable, reliable dynamic management of massive amounts of data ("big data") produced by a huge number of diverse IoT connected devices
    Reliability (e.g., for handing context/policy changes and accomplishing trust from the parts of the users)
    Scalability (e.g., as various volumes of users, resources and data may be involved in service provision)
  • Most of the IoT platform provide connectivity service…
  • This approach are useful when service is provisioned from the data coming from same location
    Data process and service execute locally (distributed cloud processing, sub-work flow, data aggregation locally)
  • This approach are useful when service is provisioned from the data coming from same location
    Data process and service execute locally (distributed cloud processing, sub-work flow, data aggregation locally)
  • Distributed system
    Local and global cloud
    Processing data near source
    Execute service near users
  • Real-time data processing and service provisioning:
    IoT devices are sources of data, they will produce massive of data, so the cloud crumble under the data weight.
    Need real-time processing of the data
    Distribution of cloud functionalities
    Due to nature of IoT it is more distributed. So some of the functionalities should be distributed over different cloud and but not only in the cloud but also edge of the IoT. So some of the cloud functionalities could be done as the devices level.
    More Distribution: Decentralised (and infrastructure-less) clouds
    Processing capabilities and data positioned closer to users
    Migration of servers to follow mobile users
    Real-time service: IoT devices are sources of data, they will produce massive of data, so the cloud crumble under the data weight.
    The sensor are resources constraint devices, in where it is hard to process the massive data and provide zero tolerant services
    need a new approach on scalable and distributed managing and processing of storage of massive data
    Need real-time processing of the data
    More dynamic and distribution: Due to nature of IoT it is more distributed. So some of the functionalities should be distributed over different cloud and but not only in the cloud but also edge of the IoT. So some of the cloud functionalities could be done as the devices level.
    More dynamic: Dynamic configuration/automated provisioning/orchestration
    Considering performance targets/constraints
    Offloading from clients/hosts to cloud
    At design and run time
    Including mobile users/apps
    The sensor are resources constraint devices, in where it is hard to process the massive data and provide zero tolerant services


  • Real-time data processing and service provisioning:
    IoT devices are sources of data, they will produce massive of data, so the cloud crumble under the data weight.
    Need real-time processing of the data
    Distribution of cloud functionalities
    Due to nature of IoT it is more distributed. So some of the functionalities should be distributed over different cloud and but not only in the cloud but also edge of the IoT. So some of the cloud functionalities could be done as the devices level.
    More Distribution: Decentralised (and infrastructure-less) clouds
    Processing capabilities and data positioned closer to users
    Migration of servers to follow mobile users
    Real-time service: IoT devices are sources of data, they will produce massive of data, so the cloud crumble under the data weight.
    The sensor are resources constraint devices, in where it is hard to process the massive data and provide zero tolerant services
    need a new approach on scalable and distributed managing and processing of storage of massive data
    Need real-time processing of the data
    More dynamic and distribution: Due to nature of IoT it is more distributed. So some of the functionalities should be distributed over different cloud and but not only in the cloud but also edge of the IoT. So some of the cloud functionalities could be done as the devices level.
    More dynamic: Dynamic configuration/automated provisioning/orchestration
    Considering performance targets/constraints
    Offloading from clients/hosts to cloud
    At design and run time
    Including mobile users/apps
    The sensor are resources constraint devices, in where it is hard to process the massive data and provide zero tolerant services


  • Internet of thing (IoT and cloud convergence opportunitis and challenges

    1. 1. IoT and Cloud Convergence: Opportunities and Challenges A. Rahim Biswas Create-Net, Italy
    2. 2. Outline  IoT and Cloud vision and requirements  Convergence approach’s  Example of existing platform  Emerging challenges of IoT/Cloud
    3. 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. 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. 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. 6. IoT Enablers Cloud
    7. 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. 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. 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. 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. 11.  Cloud-centric IoT (Bring IoT functionalities in Cloud)  IoT-Centric Cloud (Bring Cloud functionalities in IoT Convergence approach’s
    12. 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. 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. 14.  Carriots platform as a service design for IoT and M2M application Carriots Cloud platform
    15. 15. Axeda IoT Cloud Services
    16. 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. 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. 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. 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. 20. IoT-Centric cloud computing
    21. 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. 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. 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. 24. iCore Project IoT Framework
    25. 25. Thank you very much Questions abdur.rahim@create-net.org
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