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Wireless network measurement

Wireless network measurement. We’ll look at three papers Wireless LAN (WLAN) usage study at Dartmouth college Link measurement in multihop network Roofnet Packet delivery in sensor networks Medium-size sensor networks.

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Wireless network measurement

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  1. Wireless network measurement • We’ll look at three papers • Wireless LAN (WLAN) usage study • at Dartmouth college • Link measurement in multihop network • Roofnet • Packet delivery in sensor networks • Medium-size sensor networks

  2. Understanding Packet Delivery Performance in Dense Wireless Sensor Networks Jerry Zhao & Ramesh Govindan SenSys ‘03

  3. Motivation • wireless sensor networks • deployed in harsh environment • using low power radio (not much frequency diversity) • densely deployed • quantitative understanding of packet delivery • physical-layer measurement (w/o interfering transmission) • Dependence on environment, physical-layer coding scheme, and receiver? • MAC layer measurement (w/ interfering transmission) • Effect of carrier sense, MAC layer retransmission?

  4. Why focus on packet delivery? • Very basic • Packet delivery ratio determines energy efficiency & network lifetime • Poor packet delivery may degrade application performance • Important for evaluating almost all communication protocols

  5. Experiment design • Experiment environment • Indoor environment (office building) • Natural habitat • Empty parking lot • Sensor nodes • Mica motes • Experiment software

  6. Experiment environment • I: office building • 2m x 40m hallway • harsh environment: multipath reflection • H: habitat • 150m x 150m segment of a state park • downhill slope • multi-path due to foliage & rocks • O: open parking lot • 150m x 150m open parking lot • “benign” environment

  7. Sensor nodes: Mica motes • 4MHz Atmel processor, 512KB flash memory • ASK (amplitude shift keying) • low-power 433Mhz radio • omni-directional antenna • nominal throughput of 20Kbps • TinyOS • physical-layer error detection/correction • MAC: CSMA/CA, link-layer ACK

  8. Experiment software • Traffic generator • Periodic generation • Generation following a distribution • Upload experiment parameters • Information logger (in TinyOS)

  9. Packet delivery at physical layer • topology: 60 motes placed in a line • single transmitter: head of line • 0.5m apart • 0.25m apart near the edge of the comm. range • remove some nodes near the transmitter • traffic: periodic transmission, 1 pkt/sec • disable TinyOS MAC & retransmission • physical-layer coding • three coding schemes • transmit power • high, medium, low

  10. Physical layer encoding scheme • SECDED (Single Error Correction & Double Error Detection) • TinyOS default • convert each byte into 24 bits • can detect 2 bit errors & correct one bit error • Manchester encoding • convert a byte into 16 bits • detect an error out of 2 bits • 4-bit/6-bit scheme (4b6b) • encode one byte into 12 bits • detect 1 bit error out of 6 bits

  11. I H O Packet loss in three environments 4b6b coding, high Tx power

  12. H M L Packet loss with different transmit power • better delivery under lower power (possibly due to reduced multi-path problems) 4b6b coding, indoor environment

  13. Packet delivery using different coding schemes • SECDED is much better (however also consumes more bandwidth) • 4b6b & Manchester coding similar performance high tx power, indoor environment

  14. I H O How does reception rate vary with distance from the transmitter? • Gray area due to multipath problems • Width of gray area significant high tx power, 4b6b coding

  15. Are the results representative? • losses caused by multipath • difficult to be overcome by low-power radio • Low frequency diversity

  16. Implications • likelihood of links falling into gray area is high • shortest path (in hop count or geographic distance) may not be good • a long hop may have high loss rate • other bad consequences • nodes need to carefully select neighbors based on measured packet delivery rate

  17. Can signal strength predict link quality? • Unfortunately, NO Indoor, high Tx Power

  18. Can sophisticated physical layer coding mask the gray area? • Not necessarily, SECDED has the lowest effective bandwidth Theoretical calculation

  19. I O H Packet delivery correlation • I & O show noticeably higher correlation than H • Implication: at the physical layer, independent losses are a reasonable assumption

  20. Temporal characteristics of packet delivery stdev of average delivery ratios • Large variations in average reception rate • time varying packet losses in gray area in 40sec windows

  21. Packet delivery at MAC Layer • TinyOS MAC • CSMA/CA: random backoff upon carrier sense • no RTS/CTS • link layer ACK: send 4 byte ACK to the sender • retransmit up to 3 times, when there’s no ACK • Experiment methodology • fix physical-layer coding (4b6b) • three environments • topology • traffic pattern

  22. Topology • multihop network • medium transmit power • indoor office building • 62 motes, one every office • node degrees: 15-18 • open parking lot • similar topology • node degrees: 17-20 • natural habitat • 4 x 12 grid, 0.75 m between two nodes • node degrees: 6-8

  23. Traffic pattern • each node sends k packets per second • k=0.5, 1, 2, 4 pkts/sec • inter-packet interval • exponentially distributed • avoid packet synchronization • each node unicasts packets (36 bytes) to neighbors in round-robin fashion • neighbor table: periodic broadcast • not intended to model application traffic

  24. H O I Packet loss distribution w/ retransmission • many packet losses • packet losses due to environment noise or collision? • better MAC (e.g., S-MAC) is required 30% of links have loss rate > 0.5

  25. Packet delivery efficiency # of distinct pkts received / # of pkts transmitted • Efficiency low - better MAC is required

  26. indoor Asymmetry in packet delivery absolute difference of packet loss rates in two directions of a link • Significant asymmetry, should try to avoid such links

  27. Conclusions • understand packet delivery in dense sensor networks • measurement at physical & MAC layers • quantify the prevalence of gray area • pathological links: large variance in loss rate; unpredictable loss rate; asymmetric • implications • “topology control”: select links based on measurement, avoid links in gray area • better MAC

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