1 / 21

Identifying High Throughput Paths in 802.11 Mesh Networks : A Model-based Approach

Identifying High Throughput Paths in 802.11 Mesh Networks : A Model-based Approach. Theodoros Salonidis (Thomson) Michele Garetto (University of Torino) Amit Saha (Tropos) Edward Knightly (Rice University). “Hot-spot” wireless networks. Cellular-like high-speed wireless data networks

gzifa
Download Presentation

Identifying High Throughput Paths in 802.11 Mesh Networks : A Model-based Approach

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. Identifying High Throughput Paths in 802.11 Mesh Networks : A Model-based Approach Theodoros Salonidis (Thomson) Michele Garetto (University of Torino) Amit Saha (Tropos) Edward Knightly (Rice University)

  2. “Hot-spot” wireless networks • Cellular-like high-speed wireless data networks • Use 802.11 for user access and wired Internet for backbone Internet Internet 802.11 802.11 Internet Internet Internet 802.11 802.11 802.11

  3. Multi-hop wireless “mesh” networks • Aim:Low-cost / high-speed wireless access • Use 802.11 for both user access and backbone • Scale: Neighborhood to city-wide, US/Europe/Asia Internet 802.11 802.11 802.11 wireless links 802.11 802.11 802.11

  4. Multi-hop wireless “mesh” networks • Fact: 802.11 CSMA MAC protocol is used for both user access and backbone • Problem: Severe throughput imbalances and starvation Internet 802.11 802.11 802.11 wireless links 802.11 802.11 802.11

  5. Our contributions • Analytical model • Predict per-flow throughput in arbitrary topologies employing 802.11 MAC protocol. • Explain the origin of starvation in CSMA-based multi-hop wireless networks • Solution • High-throughput mesh routing

  6. Roadmap • Overview of multi-hop 802.11 model • Technique for available bandwidth computation • Comparison of existing loss-based routing metrics with new routing metric that directly computes high-throughput paths

  7. Analytical model • The “channel view” of a node: Node’s transmission collides channel busy due to activity of other nodes Node’s transmission is successful idle slot … … t • Modeled as a renewal-reward process P [eventTsoccurs] Throughput (pkt/s) = Average duration of an event (s)

  8. Analytical model • Define: = probability that the node sends a packet = conditional collision probability = conditional busy channel probability • Event probabilities Success Busy channel Idle Collision … … t

  9. General throughput formula Input rate Fraction of busy time Packet loss probability Analytical model • Throughput formula (saturated link)

  10. 1 4 2 3 50 pkt/sec 20 pkt/sec 25 pkt/sec 100 pkt/sec ( ) , min = 10 pkts/sec Path BW = Available bandwidth estimation • Inter-flow step at each node • Use measured values of fB and p on adjacent links • Compute additional input rate needed to saturate each link • Intra-flow step • Clique-based formulation to capture bandwidth sharing among links within the path

  11. Model validation • Topology • Chaska.net • 196 APs / 14 GWs • Simulation setup • 802.11b, single channel • Download/Upload traffic • Load gateways: 2Mbps

  12. Model validation Chaska download scenario Chaska upload scenario • Good match between model available BW and achieved throughput

  13. Loss-based (LB) routing metrics • ETX (MIT) • ETT (Microsoft) • IRU (UIUC) • LB metrics are load-sensitive and depend only on packet loss probability p

  14. Model Tput • Non-linear on p • Linear on fB • LB metrics Tput • Linear on p Large deviation for high busy time! Single link performance

  15. Load C->G1 Achievable unused G2 LB metrics Tput loss Achievable G1 LB metrics can pick suboptimal paths G1 ? A G2 B C

  16. AVAIL vs. LB metrics • AVAIL: model-based routing metric • Aim • Compare AVAIL with LB metrics (ETX, ETT and IRU) • Routing protocol • LQSR: link state, source routing • Each node periodically broadcasts measured fB, p • Each node uses modified Dijkstra to compute AVAIL • Simulation setup • 100 initial UDP upload flows (pick min-hop gateways) • One incoming UDP flow (50 random samples) • Rate limiting • For all metrics, incoming flow rate-limited based on model

  17. Chaska comparison • Max gateway load = 2Mbps • LB metrics = AVAIL Tput on average

  18. Manhattan topology • Topology • 14x14 / 4-neighbor • 196 APs / 10 GWs • Simulation setup • 802.11b, single channel • Upload traffic • Load gateways: (30%-100%) x maxload

  19. AVAIL metric achieves x1.5 gain on average Manhattan comparison Max gateway load = 3Mbps

  20. AVAIL metric achieves x2.4 gain on average LB metrics starve! Manhattan comparison Max gateway load: 4Mbps

  21. Conclusions • Analytical model accurately predicts available bandwidth • Busy time crucial for high throughput routing • LB metrics can pick suboptimal/starving paths • Topologies that allow spatial reuse and longer paths yield highest gains

More Related