1 / 21

Geography-informed Energy Conservation for Ad Hoc Routing

Geography-informed Energy Conservation for Ad Hoc Routing. Ya Xu, John Heidemann, Deborah Estrin ISI & UCLA Presented by: Cristian Borcea. Motivation. reduce the energy consumption in ad hoc wireless networks increase the network lifetime. Solution. identifies equivalent nodes for routing

jontae
Télécharger la présentation

Geography-informed Energy Conservation for Ad Hoc Routing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Geography-informed Energy Conservation for Ad Hoc Routing Ya Xu, John Heidemann, Deborah Estrin ISI & UCLA Presented by: Cristian Borcea

  2. Motivation • reduce the energy consumption in ad hoc wireless networks • increase the network lifetime

  3. Solution • identifies equivalent nodes for routing • based on location information • turns off unnecessary nodes

  4. Assumptions • dense node deployment • many nodes can hear each other • each node knows its location • GPS ... but better other methods

  5. Energy Model • listen:receive:transmit energy consumption • 1:1.05:1.4 or 1:1.2:1.7 • recall from last week • listen:receive:transmit times are 1:3:40 • duty cycle > 22% ==> more than 50% of energy spent in listening • energy dissipation in idle state cannot be ignored

  6. Effects of turning radio off in the idle state

  7. Determining Node Equivalence • the physical space is divided into equal size squares • based on nominal radio range • any two nodes in adjacent squares can communicate with each other • the nodes within a square are equivalent

  8. Geographical Adaptive Fidelity ( GAF ) Routing • nodes in the same grid coordinate each other • who will sleep and for how long • runs over any ad hoc routing protocol • load balancing energy usage • all nodes remain up for us long as possible

  9. GAF state transitions

  10. Node Ranking • node(active) > node(discovery) • enat1>enat2 ==> node(enat1)> node(enat2) • enat = estimated node active time • node ids break the ties

  11. Adapting to Mobility • each node estimates the time when it expects the leave the grid: engt • includes this estimation in the discovery message • other nodes sleep for min(enat, engt) • GAF-ma ( mobility adaptation ), GAF-b ( basic scheme )

  12. Simulation • ns2 + cmu's extension for 802.11 • AODV vs GAF/AODV • DSR vs GAF/DSR • 50 transit nodes ( "routers" ) • 10 traffic nodes ( sources & sinks ) • Traffic: CBR • Nominal radio range: 250

  13. Energy model - values used in simulation • WaveLAN (pre-802.11, 1995) 2Mb/s • listen:receive:transmit 1:1.2:1.6W • 0.025 when sleeping • 802.11 wireless LAN • 0.75:1.5:1.9W • 802.11 cards • 0.83:1:1.4W

  14. Network Lifetime

  15. GAF energy savings • mean energy consumption per node (E0-Et)/(n*t) • E0 initial total energy for n nodes • Et total energy after time t • results: GAF+AODV is 40% better than AODV • for both GAF-b, GAF-ma

  16. GAF-b vs GAF-ma

  17. Data Delivery Ratio

  18. Average Delay

  19. Network lifetime: GAF vs AODV

  20. Network Lifetime vs Node Density

  21. Conclusions • GAF increases the network lifetime • does not decrease the performance substantially

More Related