Enhancing Network Performance by Mimicking Human Ears in Radios

1. Making Radios More Like Human Ears Jing Zhu, Xingang Guo, L. Lily Yang, W. Steven Conner Intel Corp. Lakshman Krishnamurthy Principal Engineer Intel Corp.

2. Three points • We can improve performance by making radios like our ears • And behaving like people – talk even though you hear others • Mesh can give more bandwidth – not less • Stop working on routing and NS2!

3. Problem overview • Mesh network • An ad-hoc group of nodes relaying each other’s traffic • Logically flat hierarchy – AP mesh, station mesh, hybrid mesh • Spatial reuse – use the same channel at spatially separated locations • Enable simultaneous communications to improve overall network throughput • Applicable to large-scale wireless networks * Third party brands/names are property of their respective owners

4. Physical carrier sensing • 802.11 MAC based on CSMA/CA • CS (Carrier Sensing) to avoid interference • Carrier sensing – a station listens before transmit • Listen – sample the radio energy (interference) in the air • Carrier sensing threshold • Decide transmit or wait • Current devices – static, not independently tunable • Make the threshold tunable, and network throughput can be improved dramatically with properly tuned threshold

5. Network throughput • Large-scale 802.11 networks, in each channel Link date rate – R 11 Mbps # of simultaneous comm. – N10 X) . Network throughput (R*N) 110 Mbps • “N” determined by spatial reuse • Reuse the same channel in separated location • Tuning CS threshold can leverage spatial reuse

6. Communication model • Each data rate has its own requirement on channel quality • SNIR threshold • Spatial reuse • Properly separate simultaneous comm. • Different rates will require different separation distances • CS threshold reflects separation distance

7. Anatomy of interference B X C D A I R TX RX

8. Simulating chain network • 90-node chain, 90-hop e2e path • Tx range tuned to node distance • Measure e2e throughput while varying Pcs_t • E2e throughput changes dramatically • Optimal Pcs_t depends on data rate

9. Simulating grid network • 10x10 grid, comm. w/ immediate neighbors • Tx range tuned to node distance • Measure aggregate throughput while varying Pcs_t • E2e throughput changes dramatically • Optimal Pcs_t NOT depending on propagation environment

10. B C D A I R TX RX RTS/CTS? • Protocol exchange may fail when outside of Tx range • VCS failed to take full advantage of higher pathloss to increase spatial reuse

11. Conclusion • Properly tuned carrier sensing achieves optimal spatial reuse • Dramatically improves network throughput • Computational efficient • Complementary to RTS/CTS • Non-disruptive enhancement to 802.11 MAC • Make the carrier sensing tunable in all 802.11 devices

12. 71 70 73 B Den A Office 72 74 C Back Yard Living Room 76 75 D Lower Level 77 Upper Level Overview: Experimental evaluation of an 802.11b home mesh network • Experiments performed in house (~2000 sq. ft.) in Hillsboro, OR (August, 2003) • Topology: 8 Client Laptops and 4 AP routers • In a real home network scenario, some of the laptops would likely be replaced by other 802.11 enabled devices (e.g., DVRs, media servers, stereo systems, etc.) • Traffic: Experiments assume network traffic is not limited to Internet surfing on a broadband link • Clients share significant amount of data within the home (e.g., A/V content sharing, photo storage, data backup, etc.)

13. Multi-Hop ESS Individual Node Throughput 6 6 1.7X  3.1X  5 5 4 4 Connected! 70 (O) Throughput (Mbps) Throughput (Mbps) 70 (O) Out of range 3 3 73 (D) 5.179 73 (D) 5.182 75 (L) 75 (L) 2 2 77 (B) 77 (B) 2.686 2.679 1.8 1 1 1.572 0.85 0 0 0 Office Living Room Den Backyard Office Living Room Den Backyard Individual Node Throughput Non-Mesh BSS Individual Node Throughput

14. Non-Mesh BSS Aggregate Throughput Multi-Hop ESS Aggregate Throughput 1.3X  1.9X  2.1X  5.338 5.322 3.910 3.880 3.284 2.878 Out of range 1.994 1.520 Multi-Node Throughput

15. 2.1X  Out of range Multi-Node Throughput cont. Aggregate Throughput with 8 Clients 3.709 1.719

16. Multi-Hop ESS Client-to-Client Throughput 2.4X  3.4X  Out of range Client-to-Client Throughput Non-Mesh BSS Client-to-Client Throughput • Note: Direct client-to-client links can help here as well

17. Multi-Hop ESS End-to-End Latency ~ 2ms increase per hop Out of range Network Latency Non-Mesh BSS End-to-End Latency • Highly dependent on implementation

18. Shorter range radio hops offer higher throughput Source: Intel Corporation Source: Intel Corporation

19. Summary of home testbed Results • A multi-hop mesh is beneficial, even for a relatively small-scale home network • Multi-hop topologies: • Can be built with standard 802.11 hardware • Can improve network performance in comparison to traditional 1-hop BSS networks • These experiments used 1 radio on each AP/router; multi-radio per AP/router would allow even better performance (multi-channel)

20. Mesh test bed and Platforms • 25-35 nodes • Laptops and embbeded Xscale boards (PXA-255 and IXP425) • Boards, software available for research • Performance comparison of mesh and wireless network self organization

21. Microsoft Research Intel Topology and Transmit power have significant impact Need self-configuration algorithms

22. 802.11S MESH standardLowering the Barriers to 802.11 Mesh Deployment • Standardize Multi-Hop ESS Mesh • Interoperability • Radio/Metric-Aware L2 Routing/Switching • Security • Self-Configuration / Management • Enhance MAC Performance for Mesh • Scalability • Scheduling (managing collisions/ interference) Parallel Efforts: Major focus of new Mesh Task Group (802.11s) • Leverage 802.11i/k where possible Influence current/ future MAC enhancement efforts to improve scalability for mesh • Leverage 802.11e/n where possible • Mesh-specific MAC enhancements can be made in ESS Mesh TG

23. Thank you