1. Robust Topology Control for Indoor Wireless Sensor Networks Greg Hackmann, Octav Chipara, and Chenyang Lu SenSys 2009 S Slides from Greg Hackmann at Washington University in Saint Louis

2. Motivation  Goal: reducing transmission power while maintaining satisfactory link quality  But it’s challenging:  Links have irregular and probabilistic properties  Link quality can vary significantly over time  Human activity and multi-path effects in indoor networks 2

3. Outline  Empirical study  Algorithm  Implementation and evaluation  Conclusion 3

4. Existing Empirical Studies  Many studies explore link performance at a fixed transmission power [Srinivasan 2006], [Woo 2003], [Reijers 2004], [Zhou 2004], [Lai 2003]  [Son 2004] evaluates older Chipcon CC1000 radios  [Lin 2006] uses a indoor environment with line-of-sight  Our study considers 802.15.4-compliant CC2420 radios in an office environment 4

5. Related Topology Control Schemes  Many schemes based on theoretical radio properties [Li 2001], [Li 2005], [Blough 2006], [Gao 2008]  Power Control with Blacklisting (PCBL) [Son 2004]  Collect extensive PRR (packet reception rate) data over all links at all power levels during bootstrapping phase  Statically reduce TX power on high-quality links  Blacklist low-quality links  Adaptive Transmission Power Control (ATPC) [Lin 2006]  Offline, compute correlation between RSSI/LQI and PRR  Online, model impact of TX power at sender on RSSI/LQI at receiver 5

6. RSSI & LQI  RSSI (Received Signal Strength Indicator)  Remaining energy in the received signal  LQI (Link Quality Indicator)  CC2420 radio provides LQI following 802.15.4 standard  Can accurately reflect the packet error rate (PER) of a channel, if measured for 100 packets 6

7. Advantages of Topology Control Testbed Topology 0 dBm -15 dBm -25 dBm 7

8. Is Per-Link Topology Control Beneficial? Impact of TX power on PRR 3 of 4 links fail @ -10 dBm...... but have modest performance @ -5 dBm Insight 1: Transmission power should be set on a per- link basis to improve link quality and save energy. 8

9. What is the Impact of Transmission Power on Contention? High contention Low signal strength Insight 2: Robust topology control algorithms must avoid increasing contention under heavy network load. 9

10. Is Dynamic Power Adaptation Necessary? Link 110 -> 139 10

11. Can Link Stability Be Predicted? Long-Term Link Stability Insight 3: Robust topology control algorithms must adapt their transmission power in order to maintain good link quality and save energy. 11

12. Are Link Indicators Robust Indoors?  Two instantaneous metrics are often proposed as indicators of link reliability:  Received Signal Strength Indicator (RSSI)  Link Quality Indicator (LQI)  Can you pick an RSSI or LQI threshold that predicts whether a link has high PRR or not? 12

13. Are Link Indicators Robust Indoors? Links 106 -> 129 and 104 -> 105 RSSI threshold = -85 dBm, PRR threshold = 0.9 4% false positive rate 62% false negative rate RSSI threshold = -85 dBm, PRR threshold = 0.9 4% false positive rate 62% false negative rate RSSI threshold = -84 dBm, PRR threshold = 0.9 66% false positive rate 6% false negative rate RSSI threshold = -84 dBm, PRR threshold = 0.9 66% false positive rate 6% false negative rate Insight 4: Instantaneous LQI and RSSI are not robust estimators of link quality in all environments. 13

14. Summary of Insights 1.Set transmission power on a per-link basis 2.Avoid increasing contention under heavy network load 3.Adapt transmission power online 4.LQI and RSSI are not robust estimators of link quality in all environments 14

15. Adaptive and Robust Topology control (ART) ART: 1.Adjusts each link’s power individually 2.Detects and avoids contention at the sender 3.Tracks link qualities in a sliding window, adjusting transmission power at a per-packet granularity 4.Does not rely on LQI or RSSI as link quality estimators 1.Is simple and lightweight by design  392 bytes of RAM, 1582 bytes of ROM, often zero network overhead 15

16. ART Algorithm Outline 16 TRIAL Trying a lower power TRIAL Trying a lower power INITIALIZING Packet window filling INITIALIZING Packet window filling STEADY Link quality within threshold STEADY Link quality within threshold Packet window full Link quality above threshold Link quality goes back below threshold Link quality falls below threshold Link quality stays at/above threshold

17. Avoiding Contention  Naïve policy: When link quality falls below threshold, then increase power level  But what if this makes things worse?  Remember, higher power → more contention  Initially increase power when link quality is too low, but remember how many failures were recorded in window  If # of failures is worse than last time, then flip direction and decrease power instead 17

18. Implementation Details  Implemented using TinyOS 2.1 CVS on top of the MAC Layer Architecture [Klues 07]  Sits below routing layer -> has been tested with Collection Tree Protocol [Gnawali 2008]  Deployed on Jolley Hall testbed for three experiments:  Link-level  High contention  Data collection (not presented here) 18

19. Link-Level Performance  Selected 29 links at random from 524 detected in empirical study  Transmitted packets round-robin over each link in batches of 100, cycled for 24 hours (15000 packets/link) PRRAvg. Current Max Power56.7% ( σ = 2.5%) 17.4 mA ( σ = 0) ART58.3% ( σ = 2.1%) 14.9 mA ( σ = 0.32) 19

20. Handling High Contention  Select 10 links at random from testbed  Send packets over all 10 links simultaneously as possible (batches of 200 packets for 30 min.)  Compare again against PCBL and max-power  Also run ART without “gradient” optimization to isolate its effect on PRR 20

21. Handling High Contention Packet Reception Rate and Energy Efficiency 21 50.9% more energy efficient than max-power 50.9% more energy efficient than max-power 40.0% more energy efficient than max-power 40.0% more energy efficient than max-power

22. Handling High Contention Distribution of PRR 22

23. Conclusions  Our empirical study shows important new negative results:  RSSI and LQI are not always robust indicators of link quality indoors  Profiling links even for several hours is insufficient for identifying good links  Inherent assumptions of existing protocols!  ART is a new topology control algorithm which is robust in complex indoor environments  ART achieves better energy efficiency than max-power without bootstrapping or link starvation 23