University University of Virginia 1 Flash Flooding: Exploiting the Capture Effect for Rapid Flooding in Wireless Sensor Networks Infocom ’ 09 Rio de Janeiro, Brazil Jiakang Lu and Kamin Whitehouse Department of Computer Science University of Virginia

University University of Virginia 2 Classic WSN Algorithms Network floods are common and important operations at the heart of most wireless sensor network algorithms. –Routing tree creation –Time synchronization –Code and data dissemination –Node localization –Group formation However, network floods are costly in latency due to …

University University of Virginia 3 A B C D … neighborhood contention A B D C E G I H F CCA+MAC Delay Tx RxTx RxTx RxTx A B D C

University University of Virginia 4 … and low-duty cycle A B D C E G I H F A B C D Rx Tx Rx Tx Minimal Interpacket Spacing … … … Wake Up Sleep

University University of Virginia 5 Related Work Low-duty cycle CSMA networks –High latency of an LPL flood [Polastre 2004], [Buettner 2006] Wireless senor networks flooding –Do not explicitly optimize for latency [Heinzelman 1999], [Levis 2002], [Hui 2004] Real-time communication protocols –Point-to-Point, multicast or data collection [He 2003], [Watteyne 2006] Rapid wakeup scheduling –Requires phase synchronization [Lu 2004], [Li 2005], [Lu 2005], [Keshavarzian 2006]

University University of Virginia 6 Flash Overview The Flash flooding protocol exploits the capture effect to reduce flooding latency by eliminating neighborhood contention –Capture: a radio successfully demodulates one of multiple overlapping transmissions of the same frequency –Allow nodes to propagate the message concurrently in a flooding scenario –Propose three flooding-specific mechanisms to manage transmission concurrency

University University of Virginia 7 Outline Experiment Methodology Design of Flash Performance evaluation Conclusions

University University of Virginia 8 Evaluation Methodology VineLab testbed –48 Tmote-skys –Office environment Trace-based Simulation –Capture-aware simulation framework –Multiple Scales and densities –Statistically verified with the testbed results

University University of Virginia 9 Flash-I: Complete Concurrency Carrier sense is completely removed before transmission –No neighborhood contention Tradeoff –Significantly reduce the flooding latency –High network coverage is not guaranteed Tx X-MAC packet trainFlash-I packet train

University University of Virginia 10 Flash-I flooding example A B D C E G I H F A B C D Tx Rx Tx … A B D C Minimal Interpacket Spacing

University University of Virginia 11 Flash-II: Maintained Concurrency Flash-II achieves low flooding latency while improving the coverage of Flash-I Each node has two phases of flooding: 1) Flash-I flood With no CCA or MAC delay 2) Neighborhood rebroadcast With CCA and MAC delay (X-MAC flood) Reach any nodes that missed the first wave

University University of Virginia 12 Flash-II flooding example A B D C E G I H F A B C D Tx Rx Tx … A B D C Phase #1 = Flash-I flood … … CCA and MAC delay before local rebroadcast

University University of Virginia 13 Flash-II flooding example A B D C E G I H F A B C D Rx Tx … A B D C Phase #2 = Local rebroadcast w/ CCA and MAC dealy … … Tx … … …

University University of Virginia 14 Flash-II Scale Simulation 75%

University University of Virginia 15 Flash-II Density Simulation 70%

University University of Virginia 16 1)a small interpacket spacing (IPS) 2)a small CCA before the packet train Flash-III packet train Flash-III: Controlled Concurrency A fine balance must be achieved to exploit the capture in a flood Flash-III applies a new technique to sense the amount of transmission concurrency Tx X-MAC packet train

University University of Virginia 17 A B D C A B C D Flash-III flooding example A B D C E G I H F Rx … Tx RxTx Rx …

University University of Virginia 18 Flash-III Scale Simulation 75%

University University of Virginia 19 Flash-III Density Simulation 80%

University University of Virginia 20 Conclusions Flash is the first network flooding protocol for wireless networks that explicitly exploits the capture effect to optimize for latency. The simplicity of Flash can bring substantial performance improvement in the existing systems and have an immediate and practical impact. The empirical study of network-wide capture dynamics and the novel capture-aware simulation framework will inspire new studies on capture in the future.

University University of Virginia 21 Thank you

University University of Virginia 22 Backup slides

University University of Virginia 23 Got D! cases where capture helps A B D C E F G H I Got B! Got D!

University University of Virginia 24 Got A! cases where collision happens A B D C E F G H I Got B! ??? Got D! ???