grafting energy-harvesting leaves onto the sensornet tree
DESCRIPTION
Grafting Energy-Harvesting Leaves onto the Sensornet Tree. AUTHORS: Lohit Yervay , Bradford Campbelly , Apoorva Bansaly , Thomas Schmidz , Prabal Duttay Presenting by : Phanindar Reddy Tati. Contents:. Abstract Introduction System overview Low-Power leaf node design Evaluation - PowerPoint PPT PresentationTRANSCRIPT
Grafting Energy-Harvesting Leaves
onto the Sensornet TreeAUTHORS:
Lohit Yervay, Bradford Campbelly, Apoorva Bansaly,
Thomas Schmidz, Prabal Duttay
Presenting by:
Phanindar Reddy Tati
Abstract Introduction System overview Low-Power leaf node design Evaluation Related work Conclusion
Contents:
We study the problem of augmenting battery-powered sensornet trees with energy-harvesting leaf nodes. Our results show that leaf nodes that are smaller in size than today’s typical battery-powered sensors can harvest enough energy from ambient sources to acquire and transmit sensor readings every minute, even under poor lighting conditions. However, achieving this functionality, especially as leaf nodes scale in size, requires new platforms, protocols, and programming. Platforms must be designed around low-leakage operation, offer a richer power supply control interface for system software, and employ an unconventional energy storage hierarchy. Protocols must not only be low-power, but they must also become low-energy, which affects initial and ongoing synchronization, and periodic communications. Systems programming, and especially bootup and communications, must become low-latency, by eliminating conservative timeouts and startup dependencies, and embracing high-concurrency. Applying these principles, we show that robust, indoor, perpetual sensing is viable using off-the-shelf technology.
Abstract:
Problem: Augmenting battery-powered sensornet trees with energy- harvesting leaf nodes
Results shows leaf nodes smaller in size works fine. Need new platforms, protocols and programming Platforms:
Low leakage operation Offer richer power supply Employs energy storage hierarchy
Protocols: Low-power and low-energy protocols
Programming: Fast Boot-up Low-latency
Continued…
• ABSTRACT
Energy Harvesting operation Approaches:
EnOcean ZigBee Green Power
Energy harvesting and Mesh Networking are not exclusive , can exist in a unified network architecture.
New technologies coupled with Star topology addresses challenges in energy harvesting operation.
Existing technologies can be combined in new ways with simple protocols to achieve energy harvesting operation.
Introduction:
• ABSTRACT • INTRODUCTION
Adding stable clock and minor software improvements to existing battery powered mesh nodes prepares them to interact with energy harvesting leaf nodes.
Leaf nodes: Similar to Branch nodes No batteries Solar cells
Design Constraints: Low-leakage Low-power operation
• ABSTRACT • INTRODUCTION
Continued…
Networking problems in augmentation: Initial Synchronization Ongoing Synchronization Bi-directional communications
Challenge: Achieve low-energy operation Positive side:
low communication is possible low-energy neighbor discovery protocols available
Optimizations are required Goal: Understanding design space of low-maintenance,
high-density sensor networks
• ABSTRACT • INTRODUCTION
Continued…
Authors Showed,
With available parts, we can build solar-powered node with ultra low leakage currents
Node works in very low indoor lighting conditions Delivers data every minute Adapted existing protocols to meet challenges of the
problem
Continued…
• ABSTRACT • INTRODUCTION
Elements: Wall-powered trunk nodes Battery powered Branch nodes Energy harvesting leaf nodes
Leaf node: Integrates sensor node like ‘Epic mote’ Energy harvesting power supply Accurate time keeping
System Overview:
• INTRODUCTION • SYSTEM OVERVIEW
Continued…
• INTRODUCTION • SYSTEM OVERVIEW
Five design principles in leaf nodes:.
Minimize power transfer inefficiencies
Minimize power conversion inefficiencies
Minimize leakages
Improve energy consumption efficiency
Minimize communication cost
Continued…
• INTRODUCTION • SYSTEM OVERVIEW
Branch Nodes: Battery and Regulator Clock Identical to sensors ‘Telos’
Leaf to Branch Communications: Wakes up on a fixed period Takes a sensor reading Transmits packet Listens inbound traffic
What if a leaf node does not have power? Low duty cycle neighbor discovery protocol
Continued…
• INTRODUCTION • SYSTEM OVERVIEW
Leaf Node: Processor Radio Real-time Clock Energy Harvesting power supply
Low-power leaf node design:
• SYSTEM OVERVIEW • LOW-POWER LEAF NODE DESIGN
Processor and Radio: Epic core mote MSP430F1611 microcontroller CC2420 Radio
Real time Clock: To investigate leaf activity NXP PCF2127A RTC Excellent time keeping stability Low current draw Flexible triggering options
Continued…
• SYSTEM OVERVIEW • LOW-POWER LEAF NODE DESIGN
Hardware Operation:
Charge Startup Active
Software Operation:
Shutdown Oscillator Fast Start Optimized startup Concurrent initializations
Continued…
• SYSTEM OVERVIEW • LOW-POWER LEAF NODE DESIGN
Evaluates the viability of energy harvesting operation, characterizes typical indoor lighting conditions, demonstrates initial and ongoing synchronization, and shows that leaf and branch nodes can communicate successfully.
Energy Harvesting Operation: Demonstrates relation between irradiance and leaf node activity
Two Leaf nodes with Amorphous Solar cell | Two Leaf nodes with Crystalline Solar cell
Work: Transmit a packet and disconnect processor and radio from power supply
Exposed to varying irradiance levels from 4 indoor light sources
Question: Given certain level of radiance, what is the transmission rate of leaf node?
Evaluation :
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Continued…
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Amorphous Crystalline6.a Similar conversion factors
under fluorescent spectrum
6.b & c Exhibits more conversion in incandescent and halogen settings
6.d Similar results under LED6.e Shows indoor locations
are viable to leaf nodes6.f Daily irradiation is fine for
leaf nodes
Continued…
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Continued…
Initial Synchronization: Two techniques to synchronize leaf nodes and branch
nodes Asynchronous neighbor discovery Synchronous event triggered
Asynchronous neighbor discovery: Disco neighbor discovery protocol Leaf nodes transmits beacons, branch nodes listen Worst case discovery latency = 50mins Discovery burden is small for both nodes
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Continued…
Leaf Nodes: Transmits beacons in a 5ms window, every 60s This allows a branch node to both employ a compatible
neighbor discovery schedule and predict future transmission times
Branch Nodes: listens for beacons in 5ms window, every 245ms
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Synchronous event triggered:
Designed a simple, zero-power, light activated trigger switch
Leaf node transmits first and then branch node responds Transmission is bidirectional
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Ongoing Synchronization:
More burden on Branch node Leaf node simply transmits beacons every multiples of
60s Branch node keeps track of leaf nodes transmission times Example
Continued…
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Ongoing Synchronization:
Continued…
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Leaf to Branch Communication:
Relatively straight forward Transmits on multiples of 60s If it does not have power, skips that activity cycle
Branch to Leaf Communication:
Like sending ACK to leaf node To enable this, we modify the branch to pipeline payload reception with
transmit FIFO loading. This allows the branch node to reply with a full packet with a 0.67ms turnaround time.
Continued…
• LOW-POWER LEAF NODE DESIGN• EVALUATION
Architectures:
The canonical sensornet is the Great Duck Island deployment.
The battery-powered nodes generated a message every 5 minutes. In this work, authors show that purely energy-harvesting indoor nodes can send a message about every minute during daylight hours.
Authors extended this architecture one level further, into energy harvesting leaves, and describe how these leaves can interoperate with the existing architectures.
Related Work:
• EVALUATION• RELATED WORK
Indoor Photo-Voltaic Systems:
TwinStar is a mixed indoor-outdoor solar energy harvesting system that explores a capacitor-only energy storage design.
The idea behind TwinStar is to use energy when it is available, and thus reduce energy leakage.
Their design is practical with batteries, however, our work explores the scenario in which complete energy loss is possible.
Continued…
• EVALUATION• RELATED WORK
Batteries have a finite lifetime, they incur replacement costs, and their average power delivery scales poorly compared with indoor photovoltaic.
Today many believe that energy-harvesting holds the key to long-term, cost-effective, and sustainable sensing.
This paper shows that it is possible to augment battery powered mesh networks with energy-harvesting leaf nodes.
Authors created a new tier of sensor nodes that are free from the constraints of battery power, but still retain the many benefits of interoperating with contemporary wireless multihop mesh networks.
This work paves the way for a new tier of perpetual computing systems, shows the viability of the architectural approach, and demonstrates interoperability with existing sensor network nodes.
Conclusion:
• RELATED WORK• CONCLUSION