Decentralized Scattering of Wake-up Times in Wireless Sensor Networks

1. Decentralized Scattering of Wake-up Times in Wireless Sensor Networks Amy L. MurphyITC-IRST, Trento, Italy joint work with Alessandro Giusti, Politecnico di Milano, ItalyGian Pietro Picco, University of Trento, Italy

2. wakeup time epoch awake interval Energy Management with Duty Cycling • A common solution to save energy on sensing devices is to periodically turn them on and off • Energy saved while turned off lead to clear gains in system lifetime • We explore duty cycling at the application level, cycling communication and/or sensing • Spreading out awake times, NOT synchronizing them • Results in lifetime increase, but at a cost… s1 time

3. Cost of Duty Cycling: response time • Scenario • Distributed nodes • Mobile base station • BS queries nearby nodes • Queries repeat until a node responds • Communication duty cycled: respond only when turned on Random Wakeup Scattered Wakeup 4 transmissionsrequired 2 transmissionsrequired

4. Random Wakeup Scattered Wakeup A A A C C B B Cost of Duty Cycling: event coverage • Scenario • Distributed sensing nodes • Sensors detect events within a given radius, only when sensors are active • Duty cycle the sensing capability • Note: long wakeup intervals A C B “Less” likely todetect events “More” likely todetect events

5. All nodes discover Their wake up time, WC Wake up time of the node before them, Wprev Wake up time of the node after them, Wnext Calculate their new target wake up time Wc’=(Wprev+Wnext)/2 *  Move toward this new wakeup time in the next epoch Key Properties Process is entirely localized All nodes execute in parallel No central coordination WC Wprev Wnext WC’ Wake-up Scattering: distributed protocol A B C

6. Scattering to reduce response delay Rapid convergence to goodscattering (2-3 rounds) Increasing awake intervals No scattering.Long awake time. After scattering.33% shorter awake time. A=0.01 Average Response Delay (fraction of E) A=0.10 A=0.15 Same responsedelay A=0.50 init Scattering Iteration Number

7. Effectiveness of scattering for response delay: Different network densities No scattering.Large radio range. After scattering.10% smaller radio range. Average Response Delay (fraction of E) Range=100, 8.4 neighbors Same responsedelay Range=110, 10.1 neighbors init Scattering Iteration Number

8. Scattering to increase sensing coverage • Goal: increase percentage of events detected by scattering the awake intervals of the sensors themselves • Results are similar to those for response delay • Details in the paper After scattering,same coverage.20% smaller awake interval.

9. Sensing radius Node Node ON Pairwisecommunication Node OFF Overlappingsensing Visualization http://www.elet.polimi.it/upload/giusti/scattering

10. Scattering & Latency in Tree-based data collection on WSN • Many WSN are used to collect data at a central location by constructing an overlay tree along which data flows • Goal: low latency for data from source to sink • In terms of wake-up times, the parentshould wake up after the child to receive its data A B X C

11. Scattering and Tree Formation A B • Consider a simple tree, and the wake-up times from the perspective of X • Well scattered, but X needs to send data to C • Would be better if C wakes up immediately after X, not A • Scattering never changes the sequence of wakeup times • We introduce jumping, a simple mechanism that allows reordering in the sequence of wakeup times • After jumping, additional scattering is required • Jumping enabled if the Wnext is a child • With some probability, select next wakeup time between Wnext and Wnextnext X C A B X C

12. Reducing Latency with Jumping 4 different awake intervals Time to root not significantly affected by scattering alone Jumping to place parentsafter children results in significant improvement Reducing gap betweenwake-ups reduces latency. However…. Time to Root(lower is better) Initial Jumping Scattering Waving: reduce gap between wakeup times

13. Tradeoff between “tree” and “coverage” Reducing space betweenwake-ups reduces latency. However…. Time to Root(lower is better) …benefits of scattering reduced.Result: lower event coverage Percent Coverage(higher is better)

14. Visualization: Tree http://www.elet.polimi.it/upload/giusti/scattering

15. Discussion • Combining wakeup scattering for coverage and jumping to achieve good, tree-based data collection yields a promising complete solution • Wakeup Scattering is fully decentralized • Wake up times are determined based on local information • Epochs need not be synchronized across nodes • Simple algorithm yields significant results • Response delay: same as random wakeup times with 33% longer awake interval • Event coverage: same as random with 20% longer awake interval • Tree: scattering + jumping improve over random from 25 to 45% http://www.elet.polimi.it/upload/giusti/scattering

16. Future Directions • Modify the awake interval to meet the application needs, e.g., increased coverage • Exploit signal strength to approximate distance between sensors • Close sensors should have “more scattered” awake times • Combine jumping to improve solutions for response delay and coverage • Avoid local minima in scattering solution • Consider applying scattering at the MAC layer http://www.elet.polimi.it/upload/giusti/scattering