Enhancing Cellular Multicast Performance Using Ad Hoc Networks

1. Enhancing Cellular Multicast PerformanceUsing Ad Hoc Networks Jun Cheol Park (jcpark@cs.utah.edu) Sneha Kumar Kasera (kasera@cs.utah.edu) School of Computing University of Utah

2. Why Multicast In Cellular Networks? • Transmitting data from single sender to multiple receivers • Why not use shared nature of wireless links? • Benefits • Efficient resource management • Emergency communication Base Station

3. Receiver heterogeneity • Different, dynamic channel condition in wireless networks • Key impediment in multicast deployment Base Station

4. Impact of receiver heterogeneity • HDR BCMCS (High Data Rate Broadcast and Multicast Services) – 3G proposed standard • Fixed data rate for each service • More heterogeneity, much less average throughput

5. Outline • Combined Architecture • BCMCS + Ad hoc • Ad hoc Paths • Transmission Interference Model • Distance-2 Vertex Coloring • MIND2 Routing Algorithm • Performance Benefits • Summary

6. Combined Architecture • Each node has dual interfaces: • HDR + Wi-Fi Base Station Multicast Members BCMCS proxy 802.11 802.11 802.11 802.11 Problematic node 802.11

7. Architecture • UCAN (Unified Cellular and Ad-Hoc Network Architecture): Haiyun Luo, et al. Mobicom’ 03 • Unicast only • Considers only HDR downlink condition of proxies • Our approach • In the context of multicast • Considers achievable data rate of ad hoc path as well as HDR downlink condition

8. How to find best ad hoc paths • Achievable data rate of ad hoc path depends upon transmission interference • Transmission interference can be modeled by interference graph • Distance-2 vertex coloring • Transmission reduction factor in data rate of ad hoc path • determined by minimum Distance-2 vertex coloring

9. Transmission Interference Model receiving range transmission range 4-hop ad hoc path 1 2 3 4 5 • Minimum number of colors for distance-2 vertex coloring matches with transmission reduction factor of ad hoc path

10. Minimum Distance-2 Vertex Coloring Δ(G)= 8 where Δ(G) is maximum node degree Distance-1 Distance-2

11. Minimum Distance-2Coloring Problem • NP-complete • Minimum solutions are mostly within upper 5% of Δ(G) + 1 (By A.H. Gebremedhin, 2004) • Minimum # of colors is approximated by Δ(G) + 1

12. Effective data rate • Achievable data rate of ad hoc path  W/(Δ(G)+1) • W = achievable data rate of one-hop link • HDR data rate of proxy p = Hp • Min{W/(Δ(G)+1), Hp} MIND2 Rouging Algorithm • Find a node that has maximal value of this effective data rate

13. Example UCAN routing MIND2 routing

14. Simulation Setup in ns-2 • Implement 3G HDR BCMCS • Implement MIND2 routing algorithm • Use IEEE 802.11b, 11Mbps • Uniform distribution of 100 nodes in a cell • # of Multicast members: N=20, 40, and 60

15. Performance Gain • Goodput = Achievable throughput

16. Performance Comparison • Fluctuated better performance due to instability of UCAN

17. Conclusion & Future work • Demonstrated receiver heterogeneity problem • Modeled transmission interference using distatance-2 vertex coloring • Developed an efficient routing algorithm, MIND2 • Showed performance benefits of MIND2 • Issues for future work • Transmission interference model when links are lossy • Use of ad hoc multicast

18. Thanks! • Any questions?

20. Backup

21. More Optimization Techniques • Simple merge • If neighbor vk already has proxy p(vk), examine the value of Hp(vk) • One more lookahead • Tvk = Min {rW/(Δ(Gvk)+1), H2p(vk)}

22. Transmission interference on two ad hoc paths Distance-2 Coloring: 5 colors required

23. Transmission Sequence