IoT and Cloud Convergence: Opportunities and Challenges A. Rahim Biswas Create-Net, Italy
Nov 28, 2014
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 challenges of IoT/Cloud
"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 "
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?
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
IoT Enablers
Cloud
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)
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)
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?
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
Cloud-centric IoT (Bring IoT functionalities in Cloud)
IoT-Centric Cloud (Bring Cloud functionalities in IoT
Convergence approach’s
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
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
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 platform that leverages powerful cloud computing technologies to provide excellent data scalability, rapid visualization, and user programmable analysis.
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Cloud-centric IoT platform
IoT Cloud Platform
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Our managed devices
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Cognitive capability
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)
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)
IoT-Centric cloud computing
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)
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)
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)
iCore Project IoT Framework
Thank you very muchQuestions