In the simulation, we consider with the number of nodes is 10x10, and varying data rates:
512kbps, 1Mbps and 3Mbps to measure the throughput and end-to-end delay.
Figure 5.4 shows that under different date rates, as the number of source-destination node pairs increases, the throughput of partially overlapping channels is better than that of non-overlapping channels, since the number of simultaneous transmissions increases.
Besides, our algorithm is also better than CAEPO and CAEPO-S which use partially over-lapping channels. Since we solve the channel oscillation problem, channel assignment can be stabilized shortly, and the transmission of nodes is not interrupted, throughput can be improved. In Figure 5.4(a), the data rate is 512kbps. Our algorithm improves the ra-tio of throughput about 12% than CAEPO-S. In Figure 5.4(b), the data rate is 1Mbps.
Our algorithm improves the ratio of throughput about 18% than CAEPO-S. In Figure 5.4(c), the data rate is 3Mbps. Our algorithm improves the ratio of throughput about 26%
than CAEPO-S. Moreover, we compare the throughput of 3Mbps with the throughput of 1Mbps, we can observe that the throughput of 3Mbps does not increase, which indicates that 3Mbps is a saturated data rate. Thus, the data rate exceeding the saturated rate does not help to improve the throughput.
Figure 5.5 illustrates the end-to-end delay with varying data rates. We can observe the end-to-end delay of partially overlapping channels is lower than that of non-overlapping channels. Since we utilize all available channels can effectively reduce the network con-tention, the network latency can be decreased. Besides, our algorithm is also better than CAEPO and CAEPO-S. Since we solve the channel oscillation problem, the transmission of nodes is not interrupted, and the nodes do not need to wait for the time of channel change, end-to-end delay can be decreased. In Figure 5.5(a), the data rate is 512kbps.
Our algorithm improves the ratio of end-to-end delay about 20% than CAEPO-S. In
Fig-ure 5.5(b), the data rate is 1Mbps. Our algorithm improves the ratio of end-to-end delay about 22% than CAEPO-S. In Figure 5.5(c), the data rate is 3Mbps. Our algorithm im-proves the ratio of end-to-end delay about 21% than CAEPO-S.
0
Number of source-destination node pairs
Non-overlapping channels CAEPO
CAEPO-S
Proposed,threshold=0.7
(a) Data rate: 512kbps
0
Number of source-destination node pairs
Non-overlapping channels CAEPO
CAEPO-S
Proposed,threshold=0.7
(b) Data rate: 1Mbps
0
Number of source-destination node pairs
Non-overlapping channels CAEPO
CAEPO-S
Proposed, threshold=0.7
(c) Data rate: 3Mbps
Figure 5.4: Throughput under varying data rates
0
Number of source-destination node pairs
Non-overlapping channels CAEPO
CAEPO-S
Proposed, threshold=0.7
(a) Data rate: 512kbps
0
Number of source-destination node pairs
Non-overlapping channels CAEPO
CAEPO-S
Proposed, threshold=0.7
(b) Data rate: 1Mbps
0
Number of source-destination node pairs
Non-overlapping channels CAEPO
CAEPO-S
Proposed, threshold=0.7
(c) Data rate: 3Mbps
Figure 5.5: End-to-end delay under varying data rates
Chapter 6 Conclusion
Channel oscillation is one of the major problems in distributed channel assignment. In this thesis, we proposed a distributed channel assignment algorithm utilizing partially overlapping channels for wireless mesh networks. Our algorithm can stabilize channel allocation. The algorithm consists of two phases: priority determine phase and fixed channel assignment phase. In the priority determine phase, we modify the HELLO packet to determine the priority. In the fixed channel assignment phase, we proposed REQUEST, ACCEPT and REJECT messages to solve the channel oscillation problem. Simulation results showed that our algorithm can improve the throughput by about 19%, and reduce the end-to-end delay by about 21% compared to the previously proposed scheme.
Bibliography
[1] I. F. Akyildiz, X. Wang, and W. Wang. Wireless mesh networks: a survey. In Computer Networks, 47(4):445–487, 2005.
[2] M. Alicherry, R. Bhatia, and L. E. Li. Joint channel assignment and routing for throughput optimization in multi-radio wireless mesh networks. In Proceedings of the 11th annual international conference on Mobile computing and networking (MobiCom), pages 58–72, 2005.
[3] K. Bong-Jun, V. Misra, J. Padhye, and D. Rubenstein. Distributed channel assign-ment in multi-radio 802.11 mesh networks. In Proceedings of IEEE Wireless Com-munications and Networking Conference (WCNC), pages 3978–3983, 2007.
[4] V. Bukkapatanam, A. A. Franklin, and C. S. R. Murthy. Using partially overlapped channels for end-to-end flow allocation and channel assignment in wireless mesh networks. In Proceedings of the IEEE international conference on Communications (ICC), pages 4650–4655, 2009.
[5] M. Burton. Channel overlap calculations for 802.11b networks. Whiter paper, Cirond Technologies Inc, 2002.
[6] R. A. Calvo and J. P. Campo. Adding multiple interface support in ns-2. http:
//personales.unican.es/aguerocr/, 2007.
[7] A. Dhananjay, H. Zhang, J. Li, and L. Subramanian. Practical, distributed channel assignment and routing in dual-radio mesh networks. In Proceedings of the ACM SIGCOMM 2009 conference on Data communication, pages 99–110, 2009.
[8] Y. Ding, Y. Huang, G. Zeng, and L. Xiao. Channel assignment with partially over-lapping channels in wireless mesh networks. In Proceedings of the 4th Annual In-ternational Conference on Wireless Internet (WICON), pages 38–46, 2008.
[9] P. B. F. Duarte, Z. M. Fadlullah, K. Hashimoto, and N. Kato. Partially overlapped channel assignment on wireless mesh network backbone. In Proceedings of the IEEE Global Communications Conference (GLOBECOM), pages 1–5, 2010.
[10] M. A. Hoque, X. Hong, and F. Afroz. Multiple radio channel assignment utilizing partially overlapped channels. In Proceedings of the IEEE Global Communications Conference (GLOBECOM), pages 4737–4743, 2009.
[11] P. Kyasanur and N. H. Vaidya. Routing and interface assignment in multi-channel multi-interface wireless networks. In Proceeding of the IEEE Wireless Communica-tions and Networking Conference (WCNC), volume 4, pages 2051–2056, 2005.
[12] Y. Liu, R. Venkatesan, and C. Li. Channel assignment exploiting partially over-lapping channels for wireless mesh networks. In Proceedings of the IEEE Global Communications Conference (GLOBECOM), pages 5624–5628, 2009.
[13] Y. Liu, R. Venkatesan, and C. Li. Load-aware channel assignment exploiting par-tially overlapping channels for wireless mesh networks. In Proceedings of the IEEE Global Communications Conference (GLOBECOM), pages 1–5, 2010.
[14] A. Mishra, E. Rozner, S. Banerjee, and W. Arbaugh. Exploiting partially overlapping channels in wireless networks: turning a peril into an advantage. In Proceedings of
the ACM SIGCOMM conference on Internet Measurement, IMC ’05, pages 29–34, 2005.
[15] A. Mishra, V. Shrivastava, S. Banerjee, and W. Arbaugh. Partially overlapped chan-nels not considered harmful. In SIGMETRICS/Performance, pages 63–74, 2006.
[16] A. H. M. Rad and V. W. S. Wong. Partially overlapped channel assignment for multi-channel wireless mesh networks. In Proceedings of the IEEE International Conference on Communications (ICC), pages 3770–3775, 2007.
[17] A. Raniwala and T. cker Chiueh. Architecture and algorithms for an ieee 802.11-based multi-channel wireless mesh network. In IEEE INFOCOM, volume 3, pages 2223–2234, 2005.
[18] A. Raniwala, K. Gopalan, and T. cker Chiueh. Centralized channel assignment and routing algorithms for multi-channel wireless mesh networks. In ACM SIGMOBILE Mobile Computing and Communications Review, volume 8, pages 50–65, 2004.
[19] A. P. Subramanian, H. Gupta, S. R. Das, and J. Cao. Minimum interference channel assignment in multiradio wireless mesh networks. In IEEE Transactions on Mobile Computing, volume 7, pages 1459–1473, 2008.