Wireless Sensor Networks Kris Pister Prof EECS UC

Wireless Sensor Networks Kris Pister Prof. EECS, UC Berkeley

Outline • Technology – Quality of Service and WSN – Protocol-Agnostic Header Compression – Localization • Applications – Physician Tracking – Mobile Autonomous Sensors

Quality of Service for WSN David Zats, Thomas Watteyne L 7 L 4 L 3 HTTP ZAL TCP SOAP RSVP-TE 6 Lo. WPAN (IETF RFC 4944, IPv 6 over IEEE 802. 15. 4) L 2. 5 MPLS (IETF RFC 3031) L 2 Slotted Channel Hopping L 1 Impact IEEE 802. 15. 4 Standards Compatibility Tools for Qo. S Low-power Low-cost

Protocol-Agnostic Header Compression Travis Massey, Chris Sutardja Frame Control (2 B) Sequence Number (1 B) Destination Personal Area Network Identifier (2 B) Destination Address (2 B) Source Personal Area Network Identifier (2 B) Source Address (2 B) Frame Check Seq. /Cyclic Redundancy Check(2 B) Message Integrity Code (4 B)

Location Awareness In Wireless Networks Steven Lanzisera

Waldo Platform • Software defined radio platform • Capable of 802. 11 b/g, 802. 15. 4 configurations • Deployable in networks • We have 16 of them now 2. 4 GHz Radio 7 cm/3 in Analog to Digital Interfaces Microcontroller (on back) FPGA

Code Modulus Synchronization A REF/TX B REF/TX A RX TOF = Δt/2

Traditional approach: Received Signal Strength 80 Estimated Distance (m) 70 TOF RSS 60 50 40 30 20 10 0 0 10 20 Distance (m) 30 40

Lanzisera’s Data 80 TOF RSS Estimated Distance (m) 70 60 50 40 30 20 10 0 0 10 20 Distance (m) 30 40

Comparison to RSS

Location Tracking

This is a big deal • Real time location – Where is it right now? – Not Where was it when it went through a portal? • Peel-and-stick infrastructure – Battery-powered “readers” – Not Line powered, with ethernet • Infrastructure-free – Inter-mote ranging – Where are we all relative to each other?

Physician Tracking Sam Zats, Steven Lanzisera w/ UC Davis Medical Center Soap Dispenser Typical Hospital Clinic Room • Track physicians • Verify application of hand sanitizer • Log & warn of non-compliance

Micro autonomous air vehicles • Small air vehicles equipped with wireless sensor motes • On-board sensing, processing, and communication enables autonomous individual and swarm behaviors • Use vehicles to deploy sensor & comm. network. • Data can be collected from otherwise inaccessible locations and relayed out over a wireless network

Hybrid wireless systems • MAVs can carry & drop motes – IR, audio, image, … • Dropped motes will form an independent sensor network • Multi-hop mesh expands capabilities – Localization – Communication backhaul – Persistent observation

Objective: Cory Hall Applications in emergency response, critical infrastructure, …

Commercial Silicon Trends • Drivers – RF 4 CE 100 M 802. 15. 4 radios? • Single chip solutions – 802. 15. 4 – 802. 11 • Radios – – Lower power Smaller radios. Atmel 1. 5 mm 2 Multi-bit-rate 802. 15. 4 Steganography? • More flash, RAM – 128 k. B, 8 k. B • More powerful u. P Chip image: Kluge (Atmel) – ARM very popular – ARM Swift ~20 k gates • w/ 128 k. B flash, 8 k. B RAM < 1 mm 2 in 90 nm!

Conclusion ü BSAC technology creates new industry ü Reliable, low-power networks now available ü Commercial high-volume drivers to very low cost ü Last hardware challenge: localization solved q Next software challenges: performance, compatibility q Mini-, micro-robots rule the world ü Exciting times ahead!