Present paper aboat Internet of Things (IoT) A Vision, Architectural Elements, and Future Directions
Overall IoT vision and the technologies that will achieve the it
Application domains in IoT with a new approach in defining them
Cloud centric Internet of Things realization and challenges
Case study of data analytics on the Aneka/Azure cloud platform
Open Challenges and Future Directions
Smart environment application domains
Cloud computing
Cloud centric Internet of Things
Microsoft Azure
Internet of Things A Vision, Architectural Elements, and Future Directions
1.
2. Internet of Things (IoT):
A Vision, Architectural Elements and
Future Directions
3. The Presentation Include The Following:
▪ Introduction
▪ Overall IoT vision and the technologies that will achieve the it
▪ Application domains in IoT with a new approach in defining them
▪ Cloud centric Internet ofThings realization and challenges
▪ Case study of data analytics on the Aneka/Azure cloud platform
▪ Open Challenges and Future Directions
▪ Summary and Conclusions
5. Internet of Things for smart environment
“Interconnection of sensing and actuating devices providing
the ability to share information across platforms through a
unified framework, developing a common operating picture
for enabling innovative applications”
7. Internet revolution
People at an unprecedented scale and pace
The next revolution
Objects to create a Smart Environment
2011
More than 7 billion
2013
9 billion
2020
24 billion
Number of interconnected Devices
1.3 trillion revenue
opportunities for
mobile network
8. Rogers
Human centric
Human creativity
Exploiting ,extending capabilities
Caceres and Friday
Two critical technologies for growing infrastructure
Cloud Computing and the Internet ofThings
Ubiquitous computing in the next decade
9. Ubiquitous computing in the next decade
miniature devices having the ability to
sense, compute and communicate
wirelessly in short distances
digital
electronics
micro-
electro-
mechanical
systems
technology
wireless
communicati
ons
11. Wireless sensor networks (WSN)
Spatially distributed autonomous sensors
Monitor physical or environmental conditions
Temperature, sound, pressure
Pass their data through the network to a main location
Is built of "nodes"
Each node is connected to one (several) sensors
12. The components that make up
theWSN monitoring network
WSN hardware
WSN
communication
stack
Middleware
Secure Data
aggregation
14. Radio Frequency Identification (RFID)
• Enables design of microchips
• ForWireless data communication
• Automatic identification of anything
• They are attached
• Acting as an electronic barcode
17. Applications
Personal and
Home
• Ubiquitous healthcare
• Home monitoring
system for aged-care
• Control of home
equipment
• Home security
Enterprise
• Environmental
monitoring
• Factory security
• Factory automation
• Climate control
• Smart Environment
• Air pollution
Utilities
• Smart grid
• Smart metering
• Water network
monitoring
• Quality assurance of
drinking water
• Monitor irrigation in
agricultural land
Mobile
• Smart transportation
• Smart logistics
• Traffic management
• Efficient logistics
management
20. Cloud computing
• It is a kind of internet-based computing,
• where shared resources and information
are provided to computers and other
devices on-demand
• It is a model for enabling ubiquitous, on-
demand access to a shared pool of
configurable computing resources
22. Cloud computing: Service models
Software as a service (SaaS)
Users gain access to application software and databases
Platform as a service (PaaS)
Application developers
Infrastructure as a service (IaaS)
IaaS refers to online services that abstract user from the detail of infrastructure
23. Cloud computing: Cloud computing types
Private cloud
Is cloud infrastructure operated solely for a single organization
Public cloud
Services are rendered over a network that is open for public use
Hybrid cloud
Hybrid cloud is a composition of two or more clouds
24. Cloud centric Internet of Things
In order to realize the full potential of cloud computing a combined framework
with a cloud at the center seems to be most viable
• Flexibility
• Scalable
26. Cloud centric Internet of Things
In this section we describe the cloud platform using
ManjrasoftAneka and MicrosoftAzure platforms
Demonstrate how cloud integrates storage, computation
Furthermore, we introduce an important realm of interaction between cloud which is useful for
combining public and private clouds using Aneka
• This interaction is critical for application developers
27. Aneka cloud computing platform
• Aneka is a .NET-based application development Platform-as-a-Service (PaaS)
• It can utilize storage and compute resources of both public and private clouds
• It offers a runtime environment and a set of APIs that enable developers to build customized applications
• For the application developer, the cloud service as well as ubiquitous sensor data is hidden
29. Aneka cloud computing platform
• Automatic management of clouds for hosting and delivering IoT services as SaaS
applications
• Components are to be put in place to schedule and provision resources with a
higher level of accuracy to support IoT applications
• The autonomic management system will tightly integrate the following services
with the Aneka framework
• Accounting
• Monitoring and Profiling
• Scheduling
• Dynamic Provisioning
30. Application scheduler and Dynamic Resource
Provisioning in Aneka for IoT applications
The Aneka scheduler
assigning each resource to a task in
an application
QoS parameters and the overall
cost for the service provider
The Dynamic Resource Provisioning
For provisioning and managing
virtualised resources
In the private and public cloud
computing
Directed by the application scheduler
31. Microsoft Azure
Is a cloud computing platform and infrastructure
For building, deploying and managingApplications and Services
Provides both PaaS and IaaS services
Supports many different programming languages
MicrosoftAzure Components
Microsoft
Azure
SQL Azure
AppFabric
Azure
Marketplace
32. IoT Sensor Data Analytics SaaS using
Aneka and Microsoft Azure
Aneka can launch any number of instances on
the Azure cloud to run their applications
Tools and data needs to be shared
There are two major
Firstly, Interaction between clouds
Secondly, Data analytics and artificial
intelligence tools requires huge resources
Schematic of Aneka/Azure Interaction for data analytics application
33. IoT Sensor Data Analytics SaaS using
Aneka and Microsoft Azure
For seamless independent IoT working architecture is SaaS to be updated
One of the key design goals of IoT web application is, it would be extensible
Management Extensibility Framework (MEF)
• It is a library for creating lightweight, extensible applications
• It allows application developers to discover and use extensions with no configuration
required
• It also lets extension developers easily encapsulate code
34. Open Challenges and Future Directions
Architecture
Energy efficient
sensing
Secure
reprogrammable
networks and
Privacy
Quality of Service
New protocols
Participatory
Sensing
Data mining
GIS based
visualization
CloudComputing
International
Activities
35. Roadmap of key technological developments in the
context of IoT application domains envisioned