Complex Networks: Traffic Dynamics, Network Performance, and Network Structure
Affiliation(s)
School of Electrical & Computer Engineering, The University of Oklahoma, Tulsa, USA. Department of Computer Science, The University of Oklahoma, Norman, USA.
School of Electrical & Computer Engineering, The University of Oklahoma, Tulsa, USA. Department of Computer Science, The University of Oklahoma, Norman, USA.
ABSTRACT
This paper explores traffic dynamics and performance of complex networks. Complex networks of various structures are studied. We use node betweenness centrality, network polarization, and average path length to capture the structural characteristics of a network. Network throughput, delay, and packet loss are used as network performance measures. We investigate how internal traffic, through put, delay, and packet loss change as a function of packet generation rate, network structure, queue type, and queuing discipline through simulation. Three network states are classified. Further, our work reveals that the parameters chosen to reflect network structure, including node betweenness centrality, network polarization, and average path length, play important roles in different states of the underlying networks.
Cite this paper
Z. Hu, K. Thulasiraman and P. Verma, "Complex Networks: Traffic Dynamics, Network Performance, and Network Structure," American Journal of Operations Research, Vol. 3 No. 1, 2013, pp. 187-195. doi: 10.4236/ajor.2013.31A018.
Z. Hu, K. Thulasiraman and P. Verma, "Complex Networks: Traffic Dynamics, Network Performance, and Network Structure," American Journal of Operations Research, Vol. 3 No. 1, 2013, pp. 187-195. doi: 10.4236/ajor.2013.31A018.
References
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[1] T. Ohira and R. Sawatari, “Network Phase Transition in Computer Network Traffic Model,” Physics Review E, Vol. 58, No. 1, pp.193-195, 1998. http://dx.doi.org/10.1103/PhysRevE.58.193 [2] D. Martino, L. Dall’Asta, G. Bianconi and M. Marsili, “Congestion Phenomena on Complex Networks,” Physics Review E, Vol. 79, No. 1, 2009, Article ID: 015101. [3] P. Echenique, J. Gomez-Gardenes and Y. Moreno, “Dynamics of Jamming Transitions in Complex Networks,” Europhysics letters, Vol. 71, No. 2, 2005, pp. 325-331. [4] Z. Jiang and M. Liang, “An Efficient Weighted Routing Strategy for Scale-Fee Networks,” Modern Physics Letters B, Vol. 26, No. 29, 2012, Article ID: 1250195. http://dx.doi.org/10.1142/S0217984912501953 [5] Z.-H. Guan, L. Chen and T.-H. Qian, “Routing in Scale-Free Networks Based on Expanding Betweeness Centrality,” Physica A: Statistical Mechanics and Its Applications, Vol. 390, No. 6, 2011, pp. 1131-1138. [6] X.-G. Tang, E. W. M. Wong and Z.-X. Wu, “Integrating Network Structure and Dynamic Information for Better Routing Strategy on Scale-Free Networks,” Physica A: Statistical Mechanics and Its Applications, Vol. 388, No. 12, 2009, pp. 2547-2554. [7] J. W. Wang, L. L. Rong and L. Zhang, “Routing Strategies to Enhance Traffic Capacity for Scale-Free Networks,” The IEEE International Conference on Intelligent Computation Technology and Automation, 2008, pp. 451-455. [8] M. Tang, Z. H. Liu, X. M. Liang and P. M. Hui, “Self-Adjusting Routing Schemes for Time-Varying Traffic in Scale-Free Networks,” Physical Review E, Vol. 80, No. 2, 2009, Article ID: 026114. [9] M. Tang and T. Zhou, “Efficient Routing Strategies in Scale-Free Networks with Limited Bandwidth,” Physical Review E, Vol. 84, No. 2, 2011, Article ID: 026116. [10] S. Sreenivasan, R. Cohen, E. Lopez, Z. Toroczkai and H. E. Stanley, “Structural Bottlenecks for Communication in Networks,” Physical Review E, Vol. 75, 2007, Article ID: 036105. [11] X. Ling, M. Hu, R. Jiang and Q. Wu, “Global Dynamic Routing for Scale-Free Networks,” Physics Review E, Vol. 81, No. 1, 2010, Article ID: 016113. [12] G. Barrenetxea, B. Berefull-Lozano and M. Vetterli, “Lattice Networks: Capacity Limits, Optimal Routing, and Queuing Behavior,” IEEE/ACM Transactions on Networking, Vol. 14, No. 3, 2006, pp. 492-505. http://dx.doi.org/10.1109/TNET.2006.876187 [13] A.-L. Barabási and R. Albert, “Emergence of Scaling in Random Networks,” Science, Vol. 286, No. 5439, 1999, pp. 509-512. http://dx.doi.org/10.1126/science.286.5439.509 [14] M. Faloutsos, P. Faloutsos and C. Faloutsos, “On the Power-Law Relationships of the Internet Topology,” Computer Communication Review, Vol. 29, No. 4, 1999, pp. 41-51. http://dx.doi.org/10.1145/316194.316229 [15] A. Tizghadam and A. Leon-Garcia, “Robust Network Planning in Non Uniform Traffic Scenarios,” In: Computer Communications, Elsevier, Amsterdam, 2011 [16] A. Tizghadam and A. Leon-Garcia, “On Traffic-Aware Betweenness and Network Criticality,” Proceedings of IEEE INFOCOM, San Diego, 15-19 March 2010. [17] A. Tizghadam and A. Leon-Garcia, “A Graph Theoretical Approach to Traffic Engineering and Network Control Problem,” IEEE 21st International Teletraffic Congress, Paris, 15-17 September 2009. [18] T. Feyessa and M. Bikdash, “Measuring Nodal Contribution to Global Network Robusness,” Proceedings of IEEE Southeastcon, Nashville, 17-20 March 2011. [19] Z. P. Hu and P. K. Verma, “Improved Reliability of Free-Space Optical Mesh Networks through Topology Design,” Journal of Optical Communications and Networking, Vol. 7, No. 5, 2008, pp. 436-448. [20] Z. P. Hu and P. K. Verma, “Impact of Network Structure on Latency in Complex Networks,” The 35th IEEE Sarnoff Symposium, Newark, 21-22 May 2012. [21] Z. P. Hu and P. K. Verma, “Interplay Between Traffic Dynamics and Network Structure,” The IARIA 8th International Conference on Systems, Seville, 27 January-1 February 2013. [22] P. Erdos and A. Rényi, “On Random Graphs I,” Publicationes Mathematicae, Vol. 6, 1959, pp. 290-297. [23] R. Guimera, et al., “Optimal Network Topologies for Local Search with Congestion,” Physics Review Letters, Vol. 89, No. 24, 2002, Article ID: 248701. http://dx.doi.org/10.1103/PhysRevLett.89.248701