Supporting the Sink mobility: a case study for WSN

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Supporting the Sink mobility: a case study for WSN

  1. 1. Supporting the Sink Mobility: a case study for WSN <ul><ul><li>D.Tacconi , I.Carreras, D.Miorandi, I.Chlamtac, </li></ul></ul><ul><ul><li>CREATE-NET research centre, Trento, Italy </li></ul></ul>http://forum.toronews.net/viewtopic.php?t=240511&postdays=0&postorder=asc&start=0 <ul><ul><li>F.Chiti, R.Fantacci </li></ul></ul><ul><ul><li>DET department, University of Florence </li></ul></ul>
  2. 2. Overview <ul><ul><li>Traditional application of WSNs </li></ul></ul><ul><ul><li>Why WSN with a Mobile Sink? </li></ul></ul><ul><ul><li>Examples and Applications </li></ul></ul><ul><ul><li>Proposed Scenario and System Architecture </li></ul></ul><ul><ul><li>Simulation Results </li></ul></ul><ul><ul><li>Future Work and Conclusions </li></ul></ul>
  3. 3. WSN: Traditional Monitoring <ul><li>Physical phenomenon to be monitored: </li></ul><ul><ul><li>Microclimate monitoring </li></ul></ul><ul><ul><li>Red tree forest monitoring: </li></ul></ul><ul><ul><ul><li>Unique forests of sequoia and red trees </li></ul></ul></ul><ul><ul><ul><li>Very specific climate: 70% of H2O cycle much upper than ground level </li></ul></ul></ul><ul><ul><ul><li>Humidity monitoring </li></ul></ul></ul><ul><li>Fixed Sink, remote connection for data collection and analysis </li></ul>
  4. 4. Mobile Sensors and Data Mules <ul><li>Implementations </li></ul><ul><ul><li>Animals habits monitoring </li></ul></ul><ul><ul><li>Tree fogs, Switzerland </li></ul></ul><ul><ul><li>Zebra, Kenya Migration and behavior </li></ul></ul><ul><ul><li>Wild horses, USA Migration and behavior </li></ul></ul><ul><li>Fixed collection points, mobile nodes acting as data mules </li></ul>
  5. 5. WSN with a Mobile Sink <ul><li>WSN can be queried by car passing by </li></ul><ul><li>Intelligent Transportation System: </li></ul><ul><ul><li>Application enhanced by WSN disposed along the road, running on handheld or GPS devices </li></ul></ul>
  6. 6. Ice Detection on mountain roads <ul><li>Sensor nodes inserted in the road to sense: </li></ul><ul><ul><li>Temperature </li></ul></ul><ul><ul><li>Humidity </li></ul></ul><ul><li>Multihop communication among nodes on and along the road </li></ul><ul><li>Car computer system can in advance alert the driver of an incoming iced part of the road </li></ul><ul><li>Very simple application, increased safety for drivers </li></ul>
  7. 7. Parking lot searching Free Parking!
  8. 8. System Architecture <ul><li>Sensor Nodes (SN) </li></ul><ul><ul><li>Sensing a quantity as temperature or parking lot status (free/occupied) </li></ul></ul><ul><ul><li>Wireless capabilities </li></ul></ul><ul><ul><li>Position aware (through GPS, distributed localization, position stored) </li></ul></ul><ul><li>Vice Sink nodes (VS) </li></ul><ul><ul><li>Nodes disposed along the road </li></ul></ul><ul><ul><li>No battery limitation </li></ul></ul><ul><ul><li>Not connected among them in principle </li></ul></ul><ul><li>Mobile Sink (MS) </li></ul><ul><ul><li>A car passing by on the road </li></ul></ul><ul><ul><li>Connected with one VS at the time </li></ul></ul><ul><ul><li>GPS enabled </li></ul></ul>+ + Pos=(Lat, Long) + Pos=(Lat, Long)
  9. 9. Geographic Query Forwarding <ul><li>MS injects a query packet to the closest VS: </li></ul><ul><ul><li>Containing MS mobility information, i.e. position, speed and direction (derived by GPS) </li></ul></ul><ul><ul><li>Indicating the target region with centre coordinates and the maximum radius of interest </li></ul></ul><ul><li>Query forwarding: </li></ul><ul><ul><li>The VS starts a Greedy geographic routing toward target region , by selecting the closest SN to the destination </li></ul></ul><ul><ul><li>The previous step is performed by each SN </li></ul></ul><ul><ul><li>Once the target region is reached, localized flooding strategy performed by node closer to target region centre </li></ul></ul><ul><ul><li>The node closest to the centre, prepares Reply packet toward expected MS position </li></ul></ul>
  10. 10. Adaptive Geographic Forwarding <ul><li>Reply forwarding </li></ul><ul><ul><li>Same greedy geographic routing toward the MS expected position </li></ul></ul><ul><ul><li>The position is adapted step by step according to original MS mobility information </li></ul></ul><ul><li>Once a VS is reached the replay packet is: </li></ul><ul><ul><li>Delivered to MS, if it is in radio range </li></ul></ul><ul><ul><li>Stored for a given amount of time, waiting for the MS to pass by </li></ul></ul><ul><ul><li>Forwarded toward the next VS, following MS mobility if it has not passed by </li></ul></ul>
  11. 11. MS and Geographic Routing Is there a parking lot on that part of the town? Free/Occupied
  12. 12. <ul><li>Simulation area: </li></ul><ul><ul><li>1000x600 m ² </li></ul></ul><ul><li>1 Mobile Sink (MS) moving with random speed among Vmin and Vmax: </li></ul><ul><ul><li>Vmin = [10 ÷20] m/s </li></ul></ul><ul><ul><li>Vmax = [20 ÷35] m/s </li></ul></ul><ul><li>Nvs Vice Sinks (VSs) are equally spaced and always disconnected among them: </li></ul><ul><ul><li>Nvs = [2 ÷20] </li></ul></ul><ul><li>NxM Sensor Nodes (SNs) are disposed along a grid and connected to 4 neighbors, with communication radius R=25m: </li></ul><ul><ul><li>N = 40 </li></ul></ul><ul><ul><li>M = [1 ÷25] </li></ul></ul>Simulation set up (Omnet++)
  13. 13. Results 1/2 <ul><li>Latency of packets vs. Number of Sensors (N=40, M= [1 ÷25]), Nvs=10, Packet Delivery Ratio (PDR)>90% </li></ul>
  14. 14. Results 2/2 <ul><li>Latency of packets vs. Number of Vice Sinks ( Nvs=[2÷20]), N=40, M= 25 , Packet Delivery Ratio (PDR)>90% </li></ul>
  15. 15. Results evaluation <ul><li>Latency remains tolerable while increasing mobility and number of SNs: </li></ul><ul><ul><li>Proposed adaptive geographic routing is scalable </li></ul></ul><ul><ul><li>Latency is mainly due to the number of hops for packet delivering </li></ul></ul><ul><ul><li>Increasing mobility results in a smaller Packet Delivery Ratio (PDR), but always above 90% </li></ul></ul><ul><li>Are disconnections from the network a problem for packet delivering and latency? </li></ul><ul><ul><li>In simulations, the MS always experiences disconnections from Nvs=2 to Nvs=20 </li></ul></ul><ul><ul><li>Delay decreases with increased Nvs (less time to look for the MS along the road) </li></ul></ul><ul><ul><li>Starting from 10 VSs delay do not increase anymore and PDR is always above 90% </li></ul></ul>
  16. 16. Conclusions and Future Work <ul><li>Design of a System Architecture to support Mobile Sink querying a WSN </li></ul><ul><li>Adaptive geographic routing for packet forwarding </li></ul><ul><li>Routing technique supports MS disconnection from the network due to mobility </li></ul><ul><li>Next steps: </li></ul><ul><ul><li>Different topologies </li></ul></ul><ul><ul><li>Number of MS>1 </li></ul></ul><ul><ul><li>More complex mobility patterns </li></ul></ul><ul><ul><li>Mobility management strategies </li></ul></ul><ul><ul><li>Energy consumption evaluation </li></ul></ul><ul><ul><li>Energy aware techniques </li></ul></ul>
  17. 17. Thanks! <ul><li>David Tacconi </li></ul><ul><li>Research staff member in Pervasive Computing area at CREATE-NET research centre </li></ul><ul><li>Ph.D. candidate at the University of Florence </li></ul><ul><li>[email_address] </li></ul><ul><li>www.create-net.org/~dtacconi </li></ul>

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