applying mobility first for the internet of things · applying mobility first for the internet of...

Applying Mobility First for the

Internet of Things

»Presented by Rich Martin»WINLAB, Rutgers University

»Credit to all in the MF team

»

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The Opportunity

Today: 1 million transistors per $

Moore’s Law: # transistors on cost-effective chip doubles every 18 months

years

ComputersPer Person

103:1

1:106

Laptop

PDA

Mainframe

Mini

WorkstationPC

Cell

1:1

1:103

Bell’s Law: a new computer class emerges every 10 years

Same fabrication technology provides CMOS radios for communication and micro-sensors

Tag

History and Vision

Everything in the physical worldconnects to the Internet

• 1999 Smart Dust• 2000 Sensor Networks• 2001 EPIC • 2004 Internet of Things• 2005 Ambient Intelligence• 2009 Swarms

Not yet realized the vision.– Analogous to Memex, Hypertext, Web ~ 1985

Outline

Distinct ApproachesExperiences with Owl in Winlab Existing Limitations

Applying Mobility First for the IoTNext Steps Conclusions

Distinct Approaches

Things look like URI namespaces– Web of Things– NDN

Things are in Flatworld of unique IDs– RFID/EPIC– Mobility First – IPv6

Real systems will be hybrids

Owl Platform Layers• Application is a presentation

layer: (web, email, SMS)

• World Model works in URI space

• Solvers convert sensed ID and values to meaningful URIs

• Aggregation provides adaptation layer on ID space to IP

• Support variety of sensors

Owl Sensors

TO-PIP:Sense 1+ times a second

• Light, temperature, switches, standing water (humidity, soil moister)

Transmit 3 packets when sensed value changes

Transmit heartbeat every 30 seconds

Transmit-OnlyTO-PIP(2013)

ClassicTelosB (2004)

TO-PIP Energy Validation

Event Frequency (seconds)

Owl Application: Status and notification

Application: Laboratory Animal Monitoring

Lessons from Owl

Energy– Will need adaptation layers

Scale– Will happen, but problems are farther off

Naming – Will need both Symbolic (URI), and Flat (ID) just like today– Humans vs Machines and Concepts vs Things

Mobility across domains– Will have to support as scale happens

Security: The Elephant in the room Sensing: Important

Actuation: Very, very Important. Purposely avoided because of security

Power Limited Devices → Adaptation Layers

“The IP information adds about 100 bits to each message, which typically has a negligible impact on the response time and power requirements”

Gershenfeld, “Internet of Things” 2004

Experiences building a 10-year lifetime wireless sensor

- 1.3 uJ per unique Tx bit

- All bits transmitted and receiver times are precious (Turn off Rx → Transmit Only Protocols)

Existing networking is too heavyweight for multi-year lifetime battery powered devices

Devices connected with high power will need to run adaptation layers

Key Mobility First concepts for the IoT

Global Unique Identifiers (GUID)Network Independent

Flat space

Symbolic Name → GUID mapping (GNS) Human Readable and Management of the name space (URI style)

Identifier → Network Address (GNRS) Machine Readable, rapid translation → route-able

Scale

Overloading GUIDs Traditional Communication Devices, Content, Context Group

Mobility First Overview for the IoT

Measured read performance

Local:Global ratioLocal:Global ratio

(ms)

GNRS (Rutgers) Auspice (UMass)

Takeaway: 10-100 ms would be typical, 1 s worst case

Building Context Groups

Existing MF prototype on phones

Close: Security for the IoT!

Sensing: light-weight security Authentication, Confidentiality (but not always)

Physical layer security + rotating hash codes

Actuation: strong security needed– E.g. Vending Machine, Door locks – Authentication, Confidentiality, Authorization, Accountability

MF approach: GUIDs as public key + signed messages

Open issues: – Energy use? (Secure actuation requires high energy?) – Key Management? (Based on physical security?)

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Backup slides

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TO-PIP: Total duty cycle

Region Time I(µs) (mA)

------------------------------A 100 4B 140 2C 560 3D 80 10E 380 18F 40 3