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Challenge: Ultra-Low-Power Energy- Harvesting Active Networked Tags (EnHANTs) Authors Maria Gorlatova, Peter Kinget, Ioannis Kymissis, Dan Rubenstein,

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Presentation on theme: "Challenge: Ultra-Low-Power Energy- Harvesting Active Networked Tags (EnHANTs) Authors Maria Gorlatova, Peter Kinget, Ioannis Kymissis, Dan Rubenstein,"— Presentation transcript:

1 Challenge: Ultra-Low-Power Energy- Harvesting Active Networked Tags (EnHANTs) Authors Maria Gorlatova, Peter Kinget, Ioannis Kymissis, Dan Rubenstein, Xiaodong Wang, Gil Zussman Presenter Velin Dimitrov

2 Small Flexible Self-Reliant (energy) Attached to non-networked objects  Books, Clothing, Produce, etc. EnHANTS

3 Between sensor networks and RFID tags in capabilities EnHANTs

4 RFID -> Identify EnHANTs -> Actively search Enables continous monitoring and querying Misplaced book detector Detect people in disasters Why EnHANTs?

5 “enablers for the Internet of Things” Today computers—and, therefore, the Internet—are almost wholly dependent on human beings for information. Nearly all of the roughly 50 petabytes (a petabyte is 1,024 terabytes) of data available on the Internet were first captured and created by human beings—by typing, pressing a record button, taking a digital picture or scanning a bar code. Conventional diagrams of the Internet... leave out the most numerous and important routers of all - people. The problem is, people have limited time, attention and accuracy— all of which means they are not very good at capturing data about things in the real world. And that's a big deal. We're physical, and so is our environment... You can't eat bits, burn them to stay warm or put them in your gas tank. Ideas and information are important, but things matter much more. Yet today's information technology is so dependent on data originated by people that our computers know more about ideas than things. If we had computers that knew everything there was to know about things—using data they gathered without any help from us—we would be able to track and count everything, and greatly reduce waste, loss and cost. We would know when things needed replacing, repairing or recalling, and whether they were fresh or past their best. The Internet of Things has the potential to change the world, just as the Internet did. Maybe even more so. Internet of Things

6 Network – Multihop Ultra Low Power – nJ/bit Harvest Energy Energy Adaptive Exchange messages (IDs) Trasmit 1-10m Thin and flexible Capabilities

7 Scheduling of query responses of RFID Sensor networks IEEE 802.15.4a  Based on Impulse Radio UWB  Ranging  26 Mb/s  Backward Compatible Existing Research

8 Dynamic activation of energy-harvesting sensors Outsourcing packet retransmissions of energy restricted nodes Texas Instruments solar energy harvesting Existing Research

9 Temperature Differences Electromagnetic Energy Airflow Vibrations Solar Motion Energy Harvesting

10 Solar – 100 to 0.1 mW/cm^2 Office/retail/lab settings brighter than residential Single and polycrystalline solar cells 10-20% efficient Efficiency depends on energy availability Rigid Solar Cells

11 Organic semiconductors Constant efficiency w.r.t brightness 1.5-1% efficiency Flexible Solar Cells

12 10 cm^2 organic semiconductor cell Outdoors -> 10 mW Single bit -> 1nJ Achievable data rate is 10 Mb/s Indoors -> 10 uW Achievable data rate is 10 Kb/s Solar Energy Use Example

13 Energy captured mechanically Users have some control PVDF – 4 uJ/cm^2 per 1.5% deflection Piezoelectric Harvesting

14 10 cm^2 of material Strained 60 times/sec Generates 2.4 mW At 1nJ/bit -> 2.4 Mb/s Piezoelectric Example

15 Compact/efficient, low self discharge Ability to measure and control Rechargeable batteries  Thin-film batteries -> flexible  Supplied voltage must exceed internal chemical potential to charge  Voltage upconversion Energy Storage

16 Capacitors Receive any voltage exceeding Cycle time More difficult to add charge as the capacitor reaches capacity Self discharging Battery -> 1000 J/cm^3 Capacitor -> 1-10 J/cm^3 Energy Storage

17 C -> Energy storage capacity E -> Current energy level r -> Energy charge rate e -> Energy consumption rate Energy Abstraction

18 UWB impulse radio (IR) Current state of art (2009)  50 pJ/bit transmit  500 pJ/bit receive  100 Kb/s to 1 Mb/s Communciations

19 Conventional modulated systems require transmitter active for entire duration of signal transmission UWB uses pulses so transmit requires very little power No difference in listening to media and receiving information Communications Paradigm Shift

20 Accurate clocks consume too much energy Ultra low power ring oscillators can be used but drift significantly Protocol redesign? Clock redesign? Challenge: Inaccurate Clocks

21 Spend more energy when it is available More accurate clocks  Help other tags synchronize Run radios more to discover nodes Open research area High Power Mode

22 Tags do not maintain contact Energy use is decided on a per-tag basis Transmit/Receive duty cycling Transmit only mode for low energy Independent State - Communications

23 If tags receive and transmit cycles align, they can pair Similar to low power modes of IEEE 802.11 and Bluetooth Keep-alives are the bursts Burst frequency clock drift Paired State - Communications

24 Tags exchange (C,E,r,e) Low energy dictates how much of this info can be exchanged How this occurs exactly is key to minimizing energy Communicating State

25 Leverage the environment Synchronization via a channel always open Can be used to influence joint energy decisions Higher layer challenges  Polling/Pushing  Security/Privacy Multiple EnHANTs

26 Deterministic model Periodic energy source  Office lights Highest energy consumption rate: Energy Management and Optimization

27 Economic Production Quantity

28 10 cm^2 solar cell with 1% efficiency Dim shelf -> 50 mW/cm^2 Maximum energy consumption 2.08 uW Translates to 2.08 Kb/s throughout day at 1nJ/bit Example

29 Order point, order quantity model Stochastic Model

30 More random, fewer known parameters  Storage capacity Cannot manufacture energy, can manufacture goods Both supply and demand are stochastic Dependency of energy means tags are like a network of factories Differences with Inventory

31 Custom UWB IR transceiver on MICA2 Synchronized OOK 2.18 nJ/bit 18 kbps at 1-3 meters Bit error rate under 0.001 CSMA Energy harvesting module -> battery, solar cell, and charging circuit EnHANT Prototype

32

33 Testbed

34 ISO/IEC 14543-3-10 30 m range Wireless light switches Solar 14 byte packets 125 kbps $1.4 B sales in 2013 EnOcean


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