Internet of Things (IoT):A vision, architectural elements, and future directions
Jayavardhana Gubbi, Rajkumar Buyya, Slaven Marusic, Marimuthu Palaniswami
Maryam [email protected]
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General View
Ubiquitous Sensing in Wireless Sensor Networks
Internet of Things: sensors and actuators blend seamlessly with the environment
Information is shared across platform to develop a common operating picture(cop)
RFID tags, embedded sensors and actuator nodes
Intuitive query
This paper: cloud centric vision for worldwide implementation of internet of things
technologies/ applications/ cloud implementation using Aneka2
IndexIntroduction
Ubiquitous Computing
Definition, Trends, Elements
Application
Cloud Centric Internet of Things
IoT sensor data analytics SaaS using Aneka and Microsoft Azure
Open Challenges and Future Directions
Conclusions3
IntroductionIn IoT, many objects are in a network
Radio Frequency Identification and Sensor Networks
Information and communication systems are embedded in environment
Generate enormous amount of data
Cloud computing provide the virtual infrastructure
Smart connectivity and context aware computation
Evolve every day existing objects and embedding intelligence into our environment
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Smart connectivity
Technology should disappear from the consciousness of the user:
A shared understanding of the situation of its users and their appliances
Software architecture and pervasive communication networks
Analytic tools
Lead to smart connectivity and context-aware computation
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Internet of Things
The term IoT Kevin Ashton 1999 in supply chain management
Main goal: sense information without human aid
Harvest information from the environment and interact with physical world
Use internet standards to provide services for information transfer, analytics, applications and communications
Bluetooth, RFID, WiFi, telephonic data services
Interconnection between objects to create smart environment
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Number of interconnection of objects
In 2011: overtakes the number of people
Currently: 9 billion devices
Expected: 24 billion by 2020
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End users and
application areas based
on data
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Ubiquitous computing in the next decade
1980: human to human interface result in ubiquitous computing discipline
Mark Weiser the forefather of ubiquitous computing (ubicomp):
“The physical world that is richly and invisibly interwoven with sensors, actuators, displays, and computational elements, embedded seamlessly in the everyday objects of our lives, and connected through a continuous network” ubiquitous computing and storage owned by various owners
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Ubiquitous computing in the next decade (cont.)In contrast to Weiser, Roger propose a human centric ubicomp
“In terms of who should benefit, it is useful to think of how ubicomp technologies can be developed not for the Sal’s of the world, but for particular domains that can be set up and customized by an individual firm or organization, such as for agricultural production, environmental restoration or retailing”
Caceres and Friday:
Discuss building blocks of ubicomp and characteristics of the system
Two critical technology: Cloud computing and Internet of Things10
Ubiquitous computing in the next decade (cont.)
Micro-electro-mechanical systems (MEMS)+ Wireless communication+ Digital electronics
=Sensors, miniature devices able to sense, compute and communicate
Ubiquitous sensing is critical in realizing overall vision of ubicomp
Cloud computingPromises reliable services Act as a receiver of data Analyze and interpret the dataDynamic resource discovery
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Ubiquitous computing in the next decade (cont.)
Sensing actuating internet framework form the core technology for smart environment
Information generated will be shared to develop common operating picture
Available IoT:Large scalePlatform independentWSN infrastructureData management and processingActuatingAnalysis
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Definition
Internet oriented (middleware)
Interconnect objects with standard communication protocols
Things oriented (sensors)
Able to interact and communicate Exchange data and information sensedReacting autonomously
Semantic oriented (knowledge)
Use information and communication technology to make services more aware, interactive and efficient
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Definition
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. This is achieved by seamless ubiquitous sensing, data analytics and information representation with Cloud computing as the unifying framework
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TrendsGoogle search trends:
IoT increase
WSN decrease
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IoT elements
Hardware: sensors, actuators, embedded communication hardware
Middleware: demand storage computing tools for data analytics
Representation
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IoT elements: RFID
Enable design of microchips for wireless data communication
Passive RFID:
No battery, use the power of the reader's interrogation
Application: Supply chain management, transportation, bank cards
Active RFID:
Have battery supply and can initiate the communication
Application: Port containers for monitoring cargo17
IoT elements:WSNLow cost, low power miniature devices use in remote sensing applications
Large number of intelligent sensors enable collection, processing analysis and dissemination of information
Sensor data are shared among sensor nodes and sent to a distributed or centralized system for analytics
Hardware: sensor interfaces, processing units, transceiver units and power supply
Communication stack: ad-hoc, transmit data to the base station
Platform independent Middleware: provide access to heterogeneous sensor resources
Secure data aggregation to extend network lifetime: self healing nodes, security18
IoT elements: addressing schemeUniquely identify things and remote control
Problems:IPV4: provide geographically group identificationIPV6: heterogeneous nodes, variable data types, concurrent operation and confluence of data from devices
Routing with TCP/IP
Uniform Resource Name (URN): creates replicas of resources that can be accessed through the URL
WSN which run on a different stack compared to the internet, need a subnet gateway having a URN to process IPV6 stack
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IoT elements: Data storage and analytics
Storage, Ownership and Expiry of the data
5% of total energy
Energy efficiency and reliability
For smart monitoring and actuation using artificial intelligence techniques
Centralized infrastructure to support storage and analytics like cloud computing
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IoT elements: visualisation
Interaction of users with the environment using smart phone or tablet
Moving from 2D to 3D
More information in more meaningful way
Help policy makers to convert data to knowledge to decide
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Applications: personal and home
Individuals own network, wifi, high bandwidth
Ubiquitous healthcare
Home monitoring for elderly care
Controle home equipment and social networking
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Application: Enterprize
Information used by owners and data may be released
Environmental monitoring, smart environment
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Application: Enterprize
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Application: Utilities
Service optimization, resource management (cost and profit)
Backbone network: cellular, WiFi and Satellite communication
Smart grid and smart metering: Efficient energy consumption
Video based IoT
Water network monitoring and quality assurance of drinking water
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Application: Mobile
Smart transportationUrban trafficSupply chain managementProductivityFreight delay
Bluetooth technologyNavigation systemCar handsfree set
Logistic managementMonitoring items in transportation
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Cloud Centric IoT
Vision of IoT:
Internet centric: Internet service is the main focus & data is contributed by objectsThings centric: smart objects take the center stage
A combined framework with cloud at center
Sesing services→ storage cloudAnalytic tool developers→ software toolsArtificial intelligence experts→ data mining and machine learning tools
Clouds provide storage, computation and visualizationCombine cloudsThread and mapreduce are complex→ map the framework to cloud API→ Aneka→ read, analyze, interpret
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IoT framework with cloud in center
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End to end interaction between stakeholders
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Aneka and Azure
Aneka is a platform for deploying Clouds developing applications on top of it. It provides a runtime environment and a set of APIs that allow developers to build .NET applications that leverage their computation on either public or private clouds.
Azure is a cloud computing platform and infrastructure created by Microsoft for building, deploying, and managing applications and services through a global network of Microsoft-managed data centers.
It provides both PaaS and IaaS services and supports many different programming languages, tools and frameworks, including both Microsoft-specific and third-party software and systems.
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Aneka cloud computing platform
Management servicesAccounting, Monitoring, Profiling,Scheduling, Dynamic provisioning
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Application scheduler & resource provisioning in Aneka
Assign resources to task
According to computation and data requirement
Instantiate or terminate storage, computational or network resources
Keep tasks scheduled
With dynamic negotiation with cloud IaaS providers
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IoT Sensor data analytics SaaS using Aneka and Microsoft Azure
Aneka launch instances on Azure to run applications
Hardness:Interaction between clouds → Aneka combine resources of public and private cloudsData analytic and artificial intelligence tools are computationally demanding
Aneka worker containers are deployed as instances of Azure worker role
when a user submits an application to the Aneka Master, the job units will be scheduled by the Aneka Master by leveraging on-premises Aneka Workers, if they exist, and Aneka Worker instances on Microsoft Azure simultaneously. When Aneka Workers finish the execution of Aneka work units, they will send the results back to Aneka Master, and then Aneka Master will send the result back to the user application
Update Saas by Management Extensibility Framework (loosely-coupled plugin) 33
Aneka/ Azure interaction for data analytics application
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Key technological development
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Open Challenges and Future Directions
Architecture:
European Union Project of SENSI and IoT architecture
Address the challenges
Successfully define architecture for different applications in WSN
In this paper
based on cloud computing
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Open Challenges and Future Directions
Energy Efficient Sensing
effectively exploits spatial and temporal characteristics of the data
Compressive wireless sensing (CWS) utilizes synchronous communication to reduce the transmission power of each sensor transmitting noisy projections of data samples to a central location for aggregation
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Open Challenges and Future Directions
Secure programmable network and privacy
Disabling pushing erroneous data
Access personal information
RFID allows person tracking→ cryptographic solutions
Outside attacks→ encryption
Insider attack
Secure programming protocol→ prevent malicious installation
Security in cloud
Privacy issue of collected data 38
Open Challenges and Future Directions
Different QoS requirements→ dynamic scheduling and resource allocation
New protocols → no standard mac protocol, must be self adaptive and allow multipath routing
Participatory sensing→ people centric, localized sensing, relying on users volunteering data and inconsistent gathering lead to missing samples
Data mining→ predefined events and data anomalies> inferring local activities>detect complex events
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Open Challenges and Future Directions
GIS based visualization→ Data need preprocessing before display, new visualization schemes for the representation of heterogeneous sensors in a 3D landscape that varies temporally have to be developed
Cloud Computing
Combine services from multiple stakeholders, scaleSupport: rapid creation of applications, seamless execution of applications
harness capabilitiesResource management Cloud application scheduling
International activities40
Summary and Conclusions
Proliferation of devices with sensing and actuation functions is getting close to the vision of IoT
In this paper
a user centric cloud based model
Flexibility to meet diverse needs
scalable
Associated challenges
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Thank you
Question?
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