internet of things a vision, architectural elements, and future directions
TRANSCRIPT
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 of Things realization and challenges▪ Case study of data analytics on the Aneka/Azure cloud
platform▪ Open Challenges and Future Directions▪ Summary and Conclusions
Introduction
What is Internet of things ?RFID , Sensor network technologies Enormous amount of data Cloud copmuting
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”
Smart connectivit
y and context-aware
computation
Shared situation
users appliance
s
Software architectures pervasive networks process convey
Analytics tools
autonomous smart behavior
Internet revolution People at an unprecedented scale and paceThe next revolutionObjects to create a Smart Environment
2011More
than 7 billion2013
9 billion
202024 billion
Overtoo
k the
acual n
umber of
people
Number of interconnected Devices
1.3 trillion revenue opportunities for mobile network
RogersHuman centricHuman creativity Exploiting ,extending capabilities
Caceres and FridayTwo critical technologies for growing infrastructure Cloud Computing and the Internet of Things
Ubiquitous computing in the next decade
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 communic
ations
Wireless sensor networks (WSN)
Spatially distributed autonomous sensors Monitor physical or environmental conditionsTemperature, sound, pressure Pass their data through the network to a main location
Is built of "nodes" Each node is connected to one (several) sensors
The components that make up the WSN
monitoring network
WSN hardware
WSN communicati
on stackMiddleware Secure Data
aggregation
Radio Frequency Identification (RFID)
• Enables design of microchips • For Wireless data
communication• Automatic identification of
anything • They are attached • Acting as an electronic barcode
Other IOT Elements
IPv4
IPv6
TCP/IP
URN
URL
URC
Addressing schemesData storage and analyticsVisualization
ApplicationsPersonal 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
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
Cloud computing Characteristics
:AgilityCostDevice and location independenceMaintenanceMultitenancyPerformance ReliabilityScalability and elasticity Security
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
Cloud computing: Cloud computing types
Private cloudIs cloud infrastructure operated solely for a single organization
Public cloudServices are rendered over a network that is open for public use
Hybrid cloudHybrid cloud is a composition of two or more clouds
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
Cloud centric Internet of Things
In this section we describe the cloud platform using
Manjrasoft Aneka and Microsoft Azure platformsDemonstrate 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
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
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
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
resourcesIn the private and public cloud
computingDirected by the application
scheduler
Microsoft Azure
Is a cloud computing platform and infrastructureFor building, deploying and managing Applications and ServicesProvides both PaaS and IaaS services Supports many different programming languages
Microsoft Azure Components
Microsoft Azure SQL Azure
AppFabricAzure
Marketplace
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
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
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
Cloud Computing
International Activities