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Distributed Joint Rate Control, Resource Allocation, and Congestion Control for Throughput Optimization in Multirate Multiradio Multichannel Wireless Network with Intersession/Intrasession Network Coding

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Abstract

Wireless multihop networks are increasingly used because of their low cost and easy deployment. However, there are still many restrictions that degrade performance. Network coding has been proposed to improve the throughput of a wireless network through the characteristics of overhearing and broadcast. In this paper, we model the network utility maximization problem using a combined intrasession and intersession network coding method to improve the network utility in multiradio, multichannel, and multirate wireless network. And we propose a network throughput optimization scheme with a rate control, resource allocation and congestion control algorithm. We formulate an optimal framework reflecting wireless network environment. Also, we propose a rate selection scheme to choose the transmission rate on each node. We evaluate the proposed algorithms by simulation. The performance evaluation results show that the proposed scheme can improve throughput for network by utility optimization in a multiradio, multichannel, and multirate wireless network.

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References

  1. Dargie, W., & Poellabauer, C. (2010). Fundamentals of wireless sensor networks: Theory and practice. Hoboken: Wiley.

    Book  Google Scholar 

  2. Akyildiz, I. F., Wang, X., & Wang, W. (2005). Wireless mesh networks: A survey. Computer Networks, 47(4), 445–487.

    Article  MATH  Google Scholar 

  3. Basagni, S., Conti, M., Giordano, S., & Stojmenovic, I. (2013). Mobile ad hoc networking: The cutting edge directions (Vol. 35). Hoboken: Wiley.

    Book  Google Scholar 

  4. Ahlswede, R., Cai, N., Li, S.-Y., & Yeung, R. W. (2000). Network information flow. IEEE Transactions on Information Theory, 46(4), 1204–1216.

    Article  MathSciNet  MATH  Google Scholar 

  5. Ho, T., Médard, M., Shi, J., Effros, M., & Karger, D. R. (1998). On randomized network coding. In Proceedings of the Annual Allerton Conference on Communication Control and Computing (pp. 11–20).

  6. Koetter, R., & Médard, M. (2003). An algebraic approach to network coding. IEEE/ACM Transactions on Networking, 11(5), 782–795.

    Article  Google Scholar 

  7. Jaggi S., Langberg, M., Katti, S., Ho, T., Katabi, D., & Médard, M. (2007). Resilient network coding in the presence of byzantine adversaries. In IEEE International Conference on Computer Communications (pp. 616–624).

  8. Katti, S., Rahul, H., Hu, W., Katabi, D., Médard, M., & Crowcroft, J. (2008). XORs in the air: Practical wireless network coding. IEEE/ACM Transactions on Networking, 16(3), 497–510.

    Article  Google Scholar 

  9. Seferoglu, H., Markopoulou, A., & Ramakrishnan, K. K. (2011). I2NC: Intra-and inter-session network coding for unicast flows in wireless networks. In Proceedings IEEE INFOCOM (pp. 1035–1043).

  10. Krigslund, J., Hansen, J., Hundeboll, M., Lucani, D. E., & Fitzek, F. H. (2013). Core: Cope with more in wireless meshed networks. In Vehicular Technology Conference (VTC Spring) (pp. 1–6).

  11. Qin, C., Xian, Y., Gray, C., Santhapuri, N., & Nelakuditi, S. (2008). I²MIX: Integration of intra-flow and inter-flow wireless network coding. In IEEE Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops (pp. 1–6).

  12. Gómez, D., Rodríguez, E., Agüero, R., & Muñoz, L. (2014). Reliable communications over wireless mesh networks with inter and intra-flow network coding. In Proceedings of the 2014 Workshop on ns-3 ACM May 2014.

  13. Hansen, J., Krigslund, J., Lucani, D. E., & Fitzek, F. H. (2013). Bridging inter-flow and intra-flow network coding for video applications: Testbed description and performance evaluation. In IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks.

  14. Khreishah, A., Khalil, I., & Wu, J. (2013). Low complexity and provably efficient algorithm for joint inter and intrasession network coding in wireless networks. IEEE Transactions on Parallel and Distributed Systems, 24(10), 2015–2024.

    Article  Google Scholar 

  15. Zhu, R. (2011). Intelligent rate control for supporting real-time traffic in WLAN mesh networks. Journal of Network and Computer Applications, 34(5), 1449–1458.

    Article  Google Scholar 

  16. Kim, T.-S., Jakllari, G., Krishnamurthy, S. V., & Faloutsos, M. (2013). An integrated routing and rate adaptation framework for multi-rate multi-hop wireless networks. Wireless Networks, 19(5), 985–1003.

    Article  Google Scholar 

  17. Kim, Y., & De Veciana, G. (2009). Is rate adaptation beneficial for inter-session network coding? IEEE Journals on Selected Areas in Communications, 27(5), 635–646.

    Article  Google Scholar 

  18. Zeng, K., Yang, Z., & Lou, W. (2010). Opportunistic routing in multi-radio multi-channel multi-hop wireless networks. IEEE Transactions on Wireless Communications, 9(11), 3512–3521.

    Article  Google Scholar 

  19. Liu, H., & Gu, Y. (2012). TCP with hop-oriented network coding in multi-radio multi-channel wireless mesh networks. IET Networks, 1(3), 171–180.

    Article  Google Scholar 

  20. Radunovic, B., Gkantsidis, C., Key, P. B., & Rodriguez, P. (2010). Toward practical opportunistic routing with intra-session network coding for mesh networks. IEEE/ACM Transaction on Networking, 18(2), 420–433.

    Article  Google Scholar 

  21. Soldo, F., Markopoulou, A., & Toledo, A. L. (2010). A simple optimization model for wireless opportunistic routing with intra-session network coding. In Proceedings of the IEEE International Symposium on Network Coding (NetCod) (pp. 1–6).

  22. Palomar, D. P., & Chiang, M. (2006). A tutorial on decomposition methods for network utility maximization. IEEE Journal on Selected Areas in Communications, 24(8), 1439–1451.

    Article  Google Scholar 

  23. Bertsekas, D. P., Nedic, A., & Ozdaglar, A. E. (2003). Convex analysis and optimization. Nashua, NH: Athena Scientific.

    MATH  Google Scholar 

  24. Brucker, P. (Ed.). (2007). Scheduling algorithms. New York, NY: Springer.

    MATH  Google Scholar 

  25. Bertsekas, D. P., & Tsitsiklis, J. N. (1989). Parallel and distributed computation—Numerical methods. New Jersey, NJ: Prentice Hall.

    MATH  Google Scholar 

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0022635).

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Correspondence to Wonsik Yoon.

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Choi, G., Yoon, W. Distributed Joint Rate Control, Resource Allocation, and Congestion Control for Throughput Optimization in Multirate Multiradio Multichannel Wireless Network with Intersession/Intrasession Network Coding. Wireless Pers Commun 89, 271–287 (2016). https://doi.org/10.1007/s11277-016-3265-1

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