An Ant-based Multipath Routing Algorithm for QoS Aware Mobile Ad-hoc Networks
- 417 Downloads
- 9 Citations
Abstract
In the wireless ad-hoc network management, Quality of Service (QoS) is an important issue. Along with the QoS ensuring, another desirable property is the network reliability. In data communications, multi-path routing strategy can cope with the problem of traffic overloads while balancing the network resource consumption. In this paper, we propose a new multipath routing algorithm for QoS-sensitive multimedia services. Based on the ant colony optimization technique, the proposed algorithm can establish effective multi-paths to enhance the network reliability. According to the load balancing strategy, data packets are adaptively distributed through the established paths while maintaining an acceptable level of QoS requirement. The most important feature of the proposed approach is its adaptability to current traffic conditions. Simulation results indicate the superior performance of the proposed algorithm, while other schemes cannot offer such an attractive performance balance.
Keywords
Multipath routing algorithm Ant colony optimization Quality of Service Mobile ad-hoc networks Load balancing Network reliability Real-time decisionPreview
Unable to display preview. Download preview PDF.
References
- 1.Yarvis M. D., Zorzi M. (2008) Ad hoc networks: Special issue on energy efficient design in wireless ad hoc and sensor networks. Ad Hoc Networks 6(8): 1183–1184CrossRefGoogle Scholar
- 2.Attia, R., Rizk, R., & Mariee, M. (2009). A hybrid multi-path ant QoS routing algorithm for MANETs. International conference on wireless and optical communications networks (WOCN ’09), pp. 1–5.Google Scholar
- 3.Shokrani, H., & Jabbehdari, S. (2009). A novel ant-based QoS routing for mobile ad-hoc networks. International conference on ubiquitous and future networks (ICUFN’09), pp. 79–82.Google Scholar
- 4.Sun, X.-M., & Lv, X.-Y. (2009). Novel dynamic ant genetic algorithm for QoS routing in wireless mesh networks. International Conference on Wireless Communications, Networking and Mobile Computing (WiCom ’09), pp. 1–4.Google Scholar
- 5.Waslander S.L., Inalhan G., Tomlin C. J. (2004) Decentralized optimization via Nash bargaining. Kluwer, DordrechtGoogle Scholar
- 6.Niyato, D., & Hossain, E. (2006). A cooperative game framework for bandwidth allocation in 4G heterogeneous wireless networks. IEEE International Conference on Communications, pp. 4357–4362.Google Scholar
- 7.Srivastava V., Neel J., MacKenzie A. B., Menon R., DaSilva L. A., Hicks J. E., Reed J. H., Gilles R. P. (2005) Using game theory to analyze wireless ad hoc networks. IEEE Communications Surveys & Tutorials 7(4): 46–56CrossRefGoogle Scholar
- 8.Xiao Y., Shan X., Ren Y. (2005) Game theory models for IEEE 802.11 DCF in wireless ad hoc networks. IEEE Communications Magazine 43(3): 22–26CrossRefGoogle Scholar
- 9.Ling S., Wei W. (2009) Multi-ant-colony based multi-path routing algorithm for overlay network. Global Congress on Intelligent Systems (GCIS) 1: 188–192CrossRefGoogle Scholar
- 10.Yang, J., Lin, Y., Xiong, W., & Xu, B. (2009). Ant colony-based multi-path routing algorithm for wireless sensor networks. International Workshop on Intelligent Systems and Applications (ISA’09), pp. 1–4.Google Scholar
- 11.Liu, M., Sun, Y., Liu, R., & Huang, X. (2007). An improved ant colony QoS routing algorithm applied to mobile ad hoc networks. International conference on wireless communications, networking and mobile computing, (WiCom 2007), pp. 1641–1644.Google Scholar
- 12.Dorigo M., Gambardella L. M. (1997) Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1(1): 53–66CrossRefGoogle Scholar
- 13.Network Simulator—ns (2000). [Online]. Available: http://www.isi.edu/vint/nsnam/
- 14.Kim, S. (2010). Game theoretic multi-objective routing scheme for wireless sensor networks. Ad-hoc & Sensor Wireless Networks, 343–359.Google Scholar
- 15.Kim, S. (2009) Online energy efficient routing approach for QoS-sensitive wireless sensor networks. International conference on information networking (ICOIN’09), pp. 1– 3.Google Scholar