The Community for Technology Leaders
RSS Icon
Issue No.11 - Nov. (2013 vol.12)
pp: 2274-2288
Beatriz Lorenzo , University of Oulu, Oulu
Savo Glisic , University of Oulu, Oulu
When considering a multicell scenario with nonuniform traffic distribution in multihop wireless networks, the search for the optimum topology becomes an NP-hard problem. For such problems, exact algorithms based on exhaustive search are only useful for small toy models, so heuristic algorithms such as genetic algorithms (GA) must be used in practice. For this purpose, we present a novel sequential genetic algorithm (SGA) to optimize the relaying topology in multihop cellular networks aware of the intercell interference and the spatial traffic distribution dynamics. We encode the topologies as a set of chromosomes and special crossover and mutation operations are proposed to search for the optimum topology. The performance is measured by a fitness function that includes the throughput, power consumption and delay. Improvement in the fitness function is sequentially controlled as newer generations evolve and whenever the improvement is sufficiently increased the current topology is updated by the new one having higher fitness. Numerical results show that SGA provides both high performance improvements in the system and fast convergence (at least one order of magnitude faster than exhaustive search) in a dynamic network environment. We also demonstrate the robustness of our algorithm to the initial state of the network.
Topology, Network topology, Interference, Genetic algorithms, Heuristic algorithms, Optimization,topology control, Cellular network, dynamic traffic distribution, genetic algorithm, intercell interference, network optimization, relaying
Beatriz Lorenzo, Savo Glisic, "Optimal Routing and Traffic Scheduling for Multihop Cellular Networks Using Genetic Algorithm", IEEE Transactions on Mobile Computing, vol.12, no. 11, pp. 2274-2288, Nov. 2013, doi:10.1109/TMC.2012.204
[1] M. Nohara et al., "Mobile Multi-Hop Relay Networking in IEEE 802.16," Technical Report IEEE-C802.16-05/013, July 2005.
[2] "Broadband Radio Access Networks (BRAN); HiperMAN; Physical (PHY) Layer," Technical Report TS-102-177 V1.3.1, Feb. 2006.
[3] Y.H. Tam, R. Benkoczi, H.S. Hassanein, and S.G. Akl, "Channel Assignment for Multihop Cellular Networks: Minimum Delay," IEEE Trans. Mobile Computing, vol. 9, no. 7, pp. 1022-1034, July 2010.
[4] K.R. Jacobson and W.A. Krzymien, "System Design and Throughput Analysis for Multihop Relaying in Cellular Systems," IEEE Trans. Vehicular Technology, vol. 58, no. 8, pp. 4514-4528, Oct. 2009.
[5] B. Lorenzo and S. Glisic, "Joint Optimization of Cooperative Diversity and Spatial Reuse in Multihop Hybrid Cellular/Ad Hoc Networks," Proc. Military Comm. Conf. (MILCOM '10), pp. 499-506, Nov. 2010.
[6] G. Kannan et al., "Cross Layer Routing for Multihop Cellular Networks," Proc. 21st Int'l Conf. Advanced Information Networking and Applications Workshops, 2007.
[7] D. Zhao and T.D. Todd, "Cellular CDMA Capacity with Out-of-Band Multihop Relaying," IEEE Trans. Mobile Computing, vol. 5, no. 2, pp. 170-178, Feb. 2006.
[8] S.-J. Lin et al., "Downlink Performance and Optimization of Relay-Assisted Cellular Networks," Proc. IEEE Wireless Comm. and Networking Conf. (WCNC '09), pp. 1-6, 2009.
[9] M. Guowang Miao, N. Himayat, G.Y. Li, A.T. Koc, and S. Talwar, "Interference-Aware Energy-Efficient Power Optimization," Proc. IEEE Int'l Conf. Comm. (ICC '09), pp. 1-5, 2009.
[10] Q. Guan, F.R. Yu, S. Jiang, and G. Wei, "Prediction-Based Topology Control and Routing in Cognitive Radio Networks," Proc. IEEE INFOCOM, pp. 4443-4452, 2010.
[11] D.M. Blough, M. Leoncini, G. Resta, and P. Santi, "The K-Neighbors Approach to Interference Bounded and Symmetric Topology Control in Ad Hoc Networks," IEEE Trans. Mobile Computing, vol. 5, no. 9, pp. 1267-1282, Sept. 2006.
[12] A. Karnik and A. Kumar, "Distributed Optimal Self-Organization in Ad Hoc Wireless Sensor Networks," IEEE/ACM Trans. Networking, vol. 15, no. 5, pp. 1035-1045, Oct. 2007.
[13] F. Wang et al., "Fault Tolerant Topology Control for All-to-One and One-to-All Communication in Wireless Networks," IEEE Trans. Mobile Comp., vol. 7, no. 3, pp. 322-331, Mar. 2008.
[14] J. Wu and F. Dai, "Mobility-Sensitive Topology Control in Mobile Ad Hoc Networks," IEEE Trans. Parallel and Distributed Systems, vol. 17, no. 6, pp. 522-535, June 2006.
[15] S. Glisic and B. Lorenzo, Advanced Wireless Networks: 4G Cognitive Opportunistic and Cooperative Technology, second ed. Wiley and Sons, 2009.
[16] W.-Z. Guo et al., "Particle Swarm Optimization for the Degree-Constrained MST Problem in WSN Topology Control," Proc. Int'l Conf. Machine Learning and Cybernetics, vol. 3, pp. 1793-1798, July 2009.
[17] Z. Huang, Z. Zhang, H. Zhu, and B. Ryu, "Topology Control for Wireless Ad Hoc Networks: A Genetic Algorithm-Based Approach," Proc. First Int'l Conf. Comm. and Networking in China, pp. 1-5, Oct. 2006.
[18] S. Yang et al., "Genetic Algorithms with Immigrants and Memory Schemes for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks," IEEE Trans. on Systems, Man, and Cybernetics, Part C: Applications and Rev., vol. 40, no. 1, pp. 52-63, Jan. 2010.
[19] L. Davis, Handbook of Genetic Algorithms. Van Nostrand Reinhold, 1991.
[20] E. Bonabeau, M. Dorigo, and T. Swarm, Intelligence: From Natural to Artificial Systems. Oxford Univ., 1999.
[21] P. Popovski and H. Yomo, "Wireless Network Coding by Amplify-and-Forward for Bi-Directional Traffic Flows," IEEE Comm. Letters, vol. 11, no. 1, pp. 16-18, Jan. 2007.
[22] B. Lorenzo and S. Glisic, "Context Aware Nano Scale Modeling of Multicast Multihop Cellular Networks," IEEE/ACM Trans. Networking, vol. 21, no. 2, pp. 359-372, Apr. 2013.
[23] J.H. Holland, Adaptation Natural and Artificial Systems. MIT, 1975.
[24] Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, 1992.
[25] J.J. Grefenstette, "Genetic Algorithms for Changing Environments," Proc. Second Int'l Conf. Parallel Problem Solving Nature, pp. 137-144, 1992.
[26] M. Grant and S. Boyd, "CVX: Matlab Software for Disciplined Convex Programming,"∼boydcvx, June 2009.
[27] S. Yang, "Genetic Algorithms with Memory- and Elitism-Based Immigrants in Dynamic Environments," Evolution Computation, vol. 16, no. 3, pp. 385-416, Sept. 2008.
[28] D. Parrott and X. Li, "Locating and Tracking Multiple Dynamic Optima by a Particle Swarm Model Using Speciation," IEEE Trans. Evolutionary Computation, vol. 10, no. 4, pp. 440-458, Aug. 2006.
[29] R.W. Morrison and K.A. De Jong, "Triggered Hypermutation Revisited," Proc. Congress Evolutionary Computation, vol. 2, pp. 1025-1032, 2000.
35 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool