Ad Hoc Probe

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Ad Hoc Probe

  1. 1. AdHoc Probe: Path Capacity Probing in Wireless Ad Hoc Networks
  2. 2. Definition <ul><li>Capacity : maximum throughput that a UDP flow can get, without any cross traffic. </li></ul><ul><li>Available Bandwidth : maximum throughput that a UDP flow can get, given (stationary) cross traffic. </li></ul>
  3. 3. Ad hoc path capacity <ul><ul><li>Definition: Path capacity </li></ul></ul><ul><ul><ul><li>the data rate achieved by a UDP stream on the unloaded path (no other traffic) </li></ul></ul></ul><ul><ul><ul><li>Path capacity = “narrow link” capacity in wired net </li></ul></ul></ul><ul><ul><ul><li>Path capacity = “narrow neighborhood” capacity in ad hoc net </li></ul></ul></ul><ul><ul><li>Ad Hoc Neighborhood </li></ul></ul><ul><ul><ul><li>The minimal set of nodes that must be inactive (no tx nor receive) while a transmission takes place. </li></ul></ul></ul><ul><ul><ul><li>Equivalently, the region affected by the transmission </li></ul></ul></ul><ul><ul><ul><li>Only one pkt transmission per neighborhood </li></ul></ul></ul><ul><ul><ul><li>Neighborhoo d hops = # of hops to traverse the neighborhood </li></ul></ul></ul><ul><ul><li>N-hood Capacity = avg link data rate/ n-hood hops </li></ul></ul>
  4. 4. Neighborhood example <ul><li>Assume 802.11 with RTS/CTS is used </li></ul><ul><li>If D r = D i =250m , nodes {3,4,5, 6} are within the same n-hood; C’=C/3 </li></ul><ul><li>If D r =250m, D i =500m, nodes {2,3,4,5. 6} are in n-hood, C’=C/4 </li></ul>solid-line circle: effective receive range ( D r ) from node 4 dotted-line circle: interference range ( D i ) caused by node 4 Distance between nodes: 200m
  5. 5. Neighborhood Capacity <ul><ul><li>N-hood Cap in an ad hoc net can vary with: </li></ul></ul><ul><ul><ul><li>MAC protocol and link scheduling </li></ul></ul></ul><ul><ul><ul><li>Link interference </li></ul></ul></ul><ul><ul><ul><li>S/N ratio; </li></ul></ul></ul><ul><ul><ul><li>Tx power </li></ul></ul></ul><ul><ul><ul><li>Encoding/modulation scheme </li></ul></ul></ul><ul><ul><ul><li>Number antennas (eg MIMO) </li></ul></ul></ul><ul><ul><ul><li>Antenna directionality </li></ul></ul></ul><ul><ul><ul><li>etc </li></ul></ul></ul>
  6. 6. Why Path Capacity? <ul><ul><li>Why do we want to measure path cap? </li></ul></ul><ul><ul><ul><li>To adjust video rates; adapt end to end encoding </li></ul></ul></ul><ul><ul><ul><li>To select TCP parameters, etc </li></ul></ul></ul>
  7. 7. Example Scenario <ul><li>Internet Server is streaming traffic to user moving in ad hoc field </li></ul><ul><li>Assume autorate and smart antennas with dynamic config </li></ul><ul><li>Wireless path capacity may vary from 2Mbps to 25Mbps </li></ul><ul><li>Server must know capacity to avoid network flood!! </li></ul>
  8. 8. Ad Hoc probe: end to end measurement tool <ul><li>Statistics of packet pair (PP) at end points reveal much about path: capacity, load, buffering, and error rate </li></ul>Receiver Sender Bottleneck PP PP measure PP measure PP
  9. 9. CapProbe Background: Packet Pair Dispersion Capacity = (Packet Size) / (Dispersion) T 3 T 2 T 3 T 3 T 1 T 3 Narrowest Link 20Mbps 10Mbps 5Mbps 10Mbps 20Mbps 8Mbps
  10. 10. Issues: Compression and Expansion <ul><li>Queueing delay on the first packet => compression </li></ul><ul><li>Queueing delay on the second packet => expansion </li></ul>
  11. 11. CapProbe (Rohit et al, SIGCOMM’04) <ul><li>Key insight: a packet pair that gets through with zero queueing delay yields the exact estimate. </li></ul><ul><li>Equivalently: zero queues -> Delay Sum Min -> exact CAP </li></ul><ul><li>CapProbe uses “ Minimum Delay Sum ” filter. </li></ul>Capacity
  12. 12. Capacity Estimation in Ad Hoc Wireless Networks <ul><li>Capacity estimation in wireless net is challenging. </li></ul><ul><ul><li>Path capacity in wireless ad hoc net depends on bottleneck capacity, topology, interference, encoding, antennae, etc. </li></ul></ul><ul><ul><li>Data rate can be fixed or auto. </li></ul></ul><ul><li>Note: Previous method (Li et al, MobiCom’01) was brute force (more later) </li></ul>
  13. 13. What do we actually measure? <ul><li>The effective path capacity = maximum achievable E2E transfer rate when the channel is idle (no other users) </li></ul><ul><li>Path capacity smaller than channel raw data rate due to: </li></ul><ul><ul><li>packet header O/H, and; </li></ul></ul><ul><ul><li>interference between multiple packets in the pipeline </li></ul></ul>
  14. 14. Effective Capacity of 802.11b <ul><li>In 802.11b, RTS packet is 40 bytes, CTS and ACK packets are 39 bytes, and the MAC header of a data packet is 47 bytes, </li></ul><ul><li>the effective capacity: </li></ul><ul><li>For instance, when the data packet size is 1500 bytes and the data rate of the wireless link is 2Mbps, the effective capacity is at most </li></ul>
  15. 15. Previous Work (Li et al) <ul><li>Dr=250m, Di=500m </li></ul><ul><li>Used UDP flow stream to probe the maximum achievable throughput (brute force method) </li></ul>
  16. 16. AdHoc Probe <ul><li>Adhoc Probe employs CapProbe concepts, and it is an active one-way technique. </li></ul><ul><li>Adhoc Probe measures end-to-end effective capacity in wireless ad hoc networks. </li></ul><ul><li>End-to-end path capacity is different to bottleneck link capacity in wireless net. </li></ul>
  17. 17. One-way vs Round-trip estimates <ul><li>One-hop; 2Mbps mode </li></ul>Immediate response packet of first probing packet will conflict with the second probing packet!
  18. 18. Multihop path simulation 1 hop 2 hop 3 hop 4 hop 5 hop 6 hop 7 hop AP dispersion 2 sender back to back packets wired Internet wireless multihop dispersion 1
  19. 19. Grid Topology <ul><li>Fixed probing packet size: 1500bytes </li></ul><ul><li>Estimate capacity (a -> b) with different cross traffic rates (Poisson traffic) </li></ul>CT: horizontal direction CT: horizontal & vertical directions a b
  20. 20. Simulation of mobile hosts <ul><li>Probing the capacity of path (1 -> 6) </li></ul><ul><li>N2~5 move clockwise </li></ul><ul><li>200 samples/run, 20 runs </li></ul>
  21. 21. Simulation of mobile end hosts <ul><li>Probing the capacity of path (0 ->25) </li></ul><ul><li>Mobility: 1 m/sec; Cross Traffic: 1kbps/flow </li></ul><ul><li>200 samples/estimation; 4 samples/second </li></ul>0 600 1200 1800 2200 2600 2800 3000
  22. 22. Testbed Measurements (WiTMeMo’05) <ul><li>802.11b fixed rate (2Mbps mode); chain topology </li></ul><ul><li>802.11b auto rate; varying distance between two nodes </li></ul><ul><li>802.11b auto rate; w/ Bluetooth interference </li></ul><ul><li>802.11b fixed rate (2Mbps mode); remote probing from the Internet </li></ul>
  23. 23. Experiment Results (1) <ul><li>Fixed rate, variable hop length </li></ul>
  24. 24. Experiment Results (2) <ul><li>Auto Rate, variable distance </li></ul>
  25. 25. Experiment Results (3) <ul><li>Auto Rate, w/ Bluetooth interference </li></ul><ul><li>Varying distance between Bluetooth nodes and AdHoc Probe receiver </li></ul>
  26. 26. Experiment Results (4) <ul><li>Probing from the Internet </li></ul>
  27. 27. Summary <ul><li>Wireless Capacity estimation critical for </li></ul><ul><ul><li>Battlefield networks </li></ul></ul><ul><ul><li>Emerging commercial ad hoc nets (eg car2car) </li></ul></ul><ul><li>We have proposed AdHoc Probe to estimate e2e path capacity in ad hoc nets. </li></ul><ul><li>NS-2 simulation validates AdHoc Probe. </li></ul><ul><li>Recent measurements confirm the findings </li></ul>
  28. 28. <ul><li>Thanks! </li></ul>

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