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On Multipath Transmission Scheduling in Cognitive Radio Mesh Networks

  • Brendan Mumey
  • Xia Zhao
  • Jian Tang
  • Richard Wolff
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 51)

Abstract

Nodes in a cognitive radio mesh network comprised of secondary users may select from a set of available channels provided they do not interfere with primary users. This ability can improve overall network performance but introduces the question of how best to use these channels. Given a routing multipath M, we would like to choose which channels each link in M should use and a corresponding transmission schedule so as to maximize the end-to-end data flow rate (throughput) supported by the entire multipath. This problem is relevant to applications such as streaming video or data where a connection may be long lasting and require a high constant throughput as well as providing robust, high-speed communications in wireless mesh networks deployed in rural environments, where there are significant amounts of spectrum available for secondary use. Better transmission scheduling can lead to improved network efficiency and less network resource consumption, e.g. energy-use. The problem is hard to due the presence of both intra-flow and inter-flow interference. In this paper, we develop a new polynomial time constant-factor approximation algorithm for this problem. We also present an effective heuristic method for finding effective multipath routes. It has been shown by simulation results that the end-to-end throughput given by the proposed algorithms provide nearly twice the throughput of single path routes and that the schedules generated are close to optimal.

Keywords

Wireless mesh networks cognitive radios multipath scheduling channel assignment interference 

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References

  1. 1.
    Akyildiz, I.F., Wang, X., Wang, W.: Wireless mesh networks: a survey. Journal of Computer Networks 47(4), 445–487 (2005)CrossRefzbMATHGoogle Scholar
  2. 2.
    Akyildiz, I.F., Lee, W.-Y., Vuran, M.C., Mohanty, S.: NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Journal of Computer Networks 50(13), 2127–2159 (2007)CrossRefzbMATHGoogle Scholar
  3. 3.
    Bartal, Y., Byers, J., Raz, D.: Fast, Distributed Approximation Algorithms for Positive Linear Programming with Applications to Flow Control. SIAM Journal of Computing 33(6), 1261–1279 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Brik, V., Rozner, E., Banarjee, S., Bahl, P.: DSAP: a protocol for coordinated spectrum access. In: Proceedings of IEEE DySPAN 2005, pp. 611–614 (2005)Google Scholar
  5. 5.
    Cao, L., Zheng, H.: Distributed spectrum allocation via local bargaining. In: Proceedings of IEEE SECON 2005, pp. 475–486 (2005)Google Scholar
  6. 6.
    Hou, Y.T., Shi, Y., Sherali, H.D.: Optimal spectrum sharing for multi-hop software defined radio networks. In: Proceedings of IEEE Infocom 2007, pp. 1–9 (2007)Google Scholar
  7. 7.
    Huang, J., Berry, R.A., Honig, M.L.: Spectrum sharing with distributed interference compensation. In: Proceedings of IEEE DySPAN 2005, pp. 88–93 (2005)Google Scholar
  8. 8.
    Khalife, H., Ahuja, S., Malouch, N., Krunz, M.: Probabilistic path selection in opportunistic cognitive radio networks. In: Proceedings of IEEE Globecomm 2008, pp. 1–5 (2008)Google Scholar
  9. 9.
    Karnik, A., Iyer, A., Rosenberg, C.: Throughput-optimal Configuration of Fixed Wireless Networks. IEEE/ACM Transactions on Networking 16(5), 1161–1174 (2008)CrossRefGoogle Scholar
  10. 10.
    Kompella, S., Wieselthier, J.E., Ephremides, A., Sherali, H.D., Nguyen, G.D.: On optimal SINR-based scheduling in multihop wireless networks. IEEE/ACM Transactions on Networking 18(6), 1713–1724 (2010)CrossRefGoogle Scholar
  11. 11.
    Luo, J., Rosenberg, C., Girard, A.: Engineering Wireless Mesh Networks: Joint Scheduling, Routing, Power Control and Rate Adaptation. IEEE/ACM Transactions on Networking 18(5), 1387–1400 (2010)CrossRefGoogle Scholar
  12. 12.
    Mumey, B., Zhao, X., Tang, J., Wolff, R.: Transmission Scheduling for Routing Paths in Cognitive Radio Mesh Networks. In: Proceedings of IEEE SECON 2010, pp. 1–8 (2010)Google Scholar
  13. 13.
    Olariu, S.: An optimal greedy heuristic to color interval graphs. Inf. Process. Lett. 37(1), 21–25 (1991)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Schneider, J., Wattenhofer, R.: A new technique for distributed symmetry breaking. In: Proceeding of ACM PODC 2010, pp. 257–266 (2010)Google Scholar
  15. 15.
    Shi, Y., Hou, Y.T.: A distributed optimization algorithm for multi-hop cognitive radio networks. In: Proceedings of IEEE Infocom 2008, pp. 1292–1300 (2008)Google Scholar
  16. 16.
    Tang, J., Misra, S., Xue, G.: Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks. Journal of Computer Networks 52(11), 2148–2158 (2008)CrossRefzbMATHGoogle Scholar
  17. 17.
    Wan, P.-J.: Multiflows in multihop wireless networks. In: Proceedings of MobiHoc 2009, pp. 85–94 (2009)Google Scholar
  18. 18.
    Wang, F., Krunz, M., Cui, S.: Spectrum sharing in cognitive radio networks. In: Proceedings of IEEE Infocom 2008, pp. 1885–1893 (2008)Google Scholar
  19. 19.
    Xi, Y., Yeh, E.M.: Distributed algorithms for spectrum allocation, power control, routing, and congestion control in wireless networks. In: Proceedings of ACM MobiHoc 2007, pp. 180–189 (2007)Google Scholar
  20. 20.
    Xin, C., Xie, B., Shen, C.-C.: A novel layered graph model for topology formation and routing in dynamic spectrum access networks. In: Proceedings of IEEE DySPAN 2005, pp. 308–317 (2005)Google Scholar
  21. 21.
    Yang, Y., Kravets, R.: Contention-aware admission control for ad hoc networks. IEEE Transactions on Mobile Computing 4(4), 363–377 (2005)CrossRefGoogle Scholar
  22. 22.
    Yuan, Y., Bahl, P., Chandra, R., Moscibroda, T., Wu, Y.: Allocating dynamic time-spectrum blocks in cognitive radio networks. In: Proceedings of ACM MobiHoc 2007, pp. 130–139 (2007)Google Scholar
  23. 23.
    Zhao, Q., Tong, L., Swami, A.: Decentralized cognitive MAC for dynamic spectrum access. In: Proceedings of IEEE DySPAN 2005, pp. 224–232 (2005)Google Scholar
  24. 24.
    Zheng, H., Peng, C.: Collaboration and fairness in opportunistic spectrum access. In: Proceedings of IEEE ICC 2005, pp. 3132–3136 (2005)Google Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • Brendan Mumey
    • 1
  • Xia Zhao
    • 2
  • Jian Tang
    • 3
  • Richard Wolff
    • 2
  1. 1.Department of Computer ScienceMontana State UniversityBozemanUSA
  2. 2.Department of Electrical and Computer EngineeringMontana State UniversityBozemanUSA
  3. 3.Department of Electrical Engineering and Computer ScienceSyracuse UniversitySyracuseUSA

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