Internet of Vehicles: University of Torontochechik/courses19/csc2125/week9/... · 2019-03-20 ·...
Transcript of Internet of Vehicles: University of Torontochechik/courses19/csc2125/week9/... · 2019-03-20 ·...
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Internet of Vehicles:From Intelligent Grid to Autonomous Cars and Vehicular Clouds
Presenter: Yasaman Rohanifar MSc Student, Department of Computer Science DGP Lab, University of Toronto
March 18, 2019
University of TorontoDepartment of Computer Science
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About this paper
2Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
● 2014 IEEE World Forum on Internet of Things (WF-IoT) Conference● 159 Citations
About the Authors:
● Mario Gerla - UCLA● Eun-Kyu Lee - UCLA● Giovanni Pau - UCLA + Sorbonne● Uichin Lee - KAIST
Source: https://static1.squarespace.com/static/
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From Individual Vehicles to the Cloud
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Collection of sensor platforms (GPS, ...) → Cloud → Network of Autonomous Vehicles
Utility Function of Autonomous Vehicles: ● Prompt delivery of the passengers to destination● Maximum safety and comfort● Minimum impact on the environment
Same evolution from Sensor Web to the Internet of things!
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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From Individual Vehicles to the Cloud
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Visionary: The vehicles will be better than human drivers!● Less Pollution● Lower Delays, Smoother Traffic● Better Driver and Passenger Comfort
Handling catastrophes:● Efficient communication with other vehicles● Discover needed sources● Necessity of secure communication● Distributed Processing Environment
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
Vehicular Cloud
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Emerging Applications on Wheels
5Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
Time-Space Validity
Content Centric
Networking
Sharing Sensory
Data
Intelligent Vehicle Grid
Characteristics observed in Vehicle Applications:
● Application Content Time-Space Validity
● Content Centric Networking
● Vehicle Collaboration Sharing Sensory Data
● Intelligent Vehicle Grid and Vehicular Data
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Emerging Applications on Wheels
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● Application Content Time-Space Validity
Vehicles as rich data “prosumers”
○ Local Validity
○ Explicit Lifetime
○ Local Interest
● Time-Space validity of data → Scalability of data collection/processing/storage
● Data should be kept on the vehicle rather than uploading to the internet!
○ Enormous Spectrum Savings
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
Time-Space Validity
Content Centric
Networking
Sharing Sensory
Data
Intelligent Vehicle Grid
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Emerging Applications on Wheels
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Interest in content not the provenance!
Flooding query messages to local area
Accepting responses regardless of the identity of the provider
Content Centric Networking → Management and Control of AUVs
● AUVs travel at high speed and short distance from neighbors → Up to date info
● In case of accident, the AUV must alert the driver
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
Time-Space Validity
Content Centric
Networking
Sharing Sensory
Data
Intelligent Vehicle Grid
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Emerging Applications on Wheels
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Producing value-added services
● MobEyes: Forensics, Witnesses for traffic accidents
● CarSpeak: Direct access to neighbor car’s sensor data
Running autonomous driving applications
● Intelligent Transportation System: Exchanging traffic congestion and road conditions
constructing up-to-date road conditions database
Collaboration → Ensuring stability of autonomous fleet
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
Time-Space Validity
Content Centric
Networking
Sharing Sensory
Data
Intelligent Vehicle Grid
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Emerging Applications on Wheels
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Generated Data from Vehicles
Smart Dust + RFID Tags + Microcontrollers
Vehicular Cloud: Instantiation of Internet of Vehicles
(protocols, services, etc to make vehicle grid work)
Vehicular Cloud Architecture → Autonomous Driving
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
Time-Space Validity
Content Centric
Networking
Sharing Sensory
Data
Intelligent Vehicle
GridVehicle Grid
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Vehicular Cloud
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● Vehicular Computing
○ Conventional CC → Mobile CC → Vehicular CC○ Mobile nodes with limited resources (computing + storage)
■ Cost to upload■ Time-consuming to search and download■ Local relevance
○ Edge Computing
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Vehicular Cloud
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● Information Centric Networking
○ ICN focuses on what (content) instead of where (host)○ Uses content names instead of IP addresses so that the
■ DONA (Data-Oriented Network Architecture)■ PSIRP (Publish-Subscribe Internet Routing Paradigm)■ NetInf (Network of Information)■ NDN (Named Data Networking)
● Interest from consumers● Data from publishers● Content name for routing
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Vehicular Cloud
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● Cloud Resources
○ Internet Cloud Vs. Vehicular Cloud ■ Storage, Sensor, Computing■ Inter-networked resources
via purely p2p connections■ Negotiating the level
Of resource sharing (brokers)■ RSUs as stationery
good negotiator role
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Vehicular Cloud
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Case Study
1. Cloud resource discovery
2. Cloud formation
3. Task assignment & result collection
4. Content publishing & sharing
5. Cloud maintenance (?)
6. Cloud Release
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Vehicular Cloud and AUV Challenges
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● NDN Network Layer
○ VCC’s “narrow waist” network layer is NDN○ Content found by exploiting geographic relevance more than naming hierarchy
● Beacons and Alarms
○ Sensors alone are not sufficient■ Maintaining stable operations in high speeds■ Extremely reduced inter-vehicle spacing
○ V2V communications are necessary■ Lead cars facing 4-stop intersections■ Finding out about road conditions ahead
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Vehicular Cloud and AUV Challenges
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● Intelligent Transport○ Using the existing highway network more efficiently○ Managing automatic charges○ Awareness of other mobiles sharing the road
● Infrastructure Failure Recovery○ Gray period of human takeover○ Losing knowledge of neighbors beyond sensor range○ Maintaining a V2V supported propagation of traffic conditions and congestion
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Vehicular Cloud and AUV Challenges
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● File and Media Downloading○ Entertainment - Marketing Strategy○ Bittorrent techniques via V2V support○ Broadcast only supported by V2V communications○ LTE would introduce too much latency and would not scale
● Cognitive Radios and Spectrum Data-base Crowdsourcing○ Need for V2V between AUVs○ DSRC 75 Mhz spectrum exhausted by the basic safety applications○ V2V requirements supported by the WIFI spectrum
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Vehicular Cloud and AUV Challenges
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● Virtualization○ AUVs might need to do “data mining”
■ Expensive computations must go to cloud■ Privacy of the drivers + sensitivity of the application
○ Customization of the sensor platform to different applications
● Security○ DDoS, Privacy, Confidentiality○ Attacks targeting the steering or the brakes system○ Access to the cars’ internal mechanism
■ On-Board Diagnostics (OBD) & CAN○ Multi-factor protection strategy
Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds
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Summary
P3 Vehicular Cloud and AUV Challenges
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P2Vehicular Cloud, the equivalent of Internet Cloud for vehicles
the core system environment that makes the evolution possible
P1Evolution of o the Internet of Autonomous Vehicles
communications, storage, intelligence and learning capabilities
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Thank you for your attention!
Questions?
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Discussion Points/Questions
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Q2 Security and Safety, Adversarial Attacks
Q1 Is Information Centric Networking secure enough?
Q2How does self-organizing cloud take place?
What about Cloud maintenance if there’s no other candidate?