Opportunistic Routing for Time-Variety and Load-Balance over Wireless Sensor Networks
ABSTRACT
To aware the topology of wireless sensor networks (WSN) with time-variety, and load-balance the resource of communication and energy, an opportunistic routing protocol for WSN based on Opportunistic Routing Entropy and ant colony optimization, called ACO-TDOP, is proposed. At first, based on the second law of thermo-dynamics, we introduce the concept of Opportunistic Routing Entropy which is a parameter representing the transmission state of each node by taking into account the power left and the distance to the sink node. Then, it is proved that the problem of route thinking about Opportunistic Routing Entropy is shown to be NP-hard. So the protocol, ACO-TDOP, is proposed. At last, numerical results confirm that the ACO-TDOP is energy conservative and throughput gainful compared with other two existing routing protocols, and show that it is efficacious to analyze and uncover fundamental of message transmission with Opportunistic Routing in wireless network using the second law of thermodynamics.
To aware the topology of wireless sensor networks (WSN) with time-variety, and load-balance the resource of communication and energy, an opportunistic routing protocol for WSN based on Opportunistic Routing Entropy and ant colony optimization, called ACO-TDOP, is proposed. At first, based on the second law of thermo-dynamics, we introduce the concept of Opportunistic Routing Entropy which is a parameter representing the transmission state of each node by taking into account the power left and the distance to the sink node. Then, it is proved that the problem of route thinking about Opportunistic Routing Entropy is shown to be NP-hard. So the protocol, ACO-TDOP, is proposed. At last, numerical results confirm that the ACO-TDOP is energy conservative and throughput gainful compared with other two existing routing protocols, and show that it is efficacious to analyze and uncover fundamental of message transmission with Opportunistic Routing in wireless network using the second law of thermodynamics.
Cite this paper
nullN. Ding, G. Tan and W. Zhang, "Opportunistic Routing for Time-Variety and Load-Balance over Wireless Sensor Networks," Wireless Sensor Network, Vol. 2 No. 9, 2010, pp. 718-723. doi: 10.4236/wsn.2010.29087.
nullN. Ding, G. Tan and W. Zhang, "Opportunistic Routing for Time-Variety and Load-Balance over Wireless Sensor Networks," Wireless Sensor Network, Vol. 2 No. 9, 2010, pp. 718-723. doi: 10.4236/wsn.2010.29087.
References
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[1] D. Tse and S. Hanly, “Multi-Access Fading Channels: Polymatroid Structure, Optimal Resource Allocation and Throughput Capacities,” IEEE Transactions on Information Theory, Vol. 44, No. 7, 1998, pp.2796-2815. [2] J. Lian, K. Naik and G. Agnew, “Data Capacity Improvement of Wireless Sensor Networks Using Non-Uniform Sensor Distribution,” Journal of Distributed Sensor Networks, Vol. 2, 2006, pp.121-145. [3] S. Biswas and R. Morris, “ExOR: Opportunistic Multi- Hop Routing for Wireless Networks,” Proceeding of ACM SIGCOMM 05, ACM Press, Pennsylvania, pp. 133- 143, 2005. [4] H. F. Hu and Z. Yang, “Collaborative Opportunistic Routing in Wireless Sensor Networks,” Journal on Communications, Vol. 30, No. 8, 2009, pp.116-123. [5] C. Luk, W. Lau and O. Yue, “An Analysis of Opportunistic Routing in Wireless Mesh Network,” Proceeding of IEEE International Conference on Communications, Beijing, 2008, pp. 2877- 2883. [6] S. Flody, V. Jacobson, et al. “A Reliable Multicast Framework for Light-Weight Sessions and Application Level Framing,” IEEE/ACM Transactions on Networking, Vol. 5, No. 6, 1997, pp.784-803. [7] K. Zeng, W. J. Lou, et al. “Capacity of Opportunistic Routing in Multi-Rate and Multi-Hop Wireless Networks,” IEEE transactions on wireless communication, Vol. 7, No. 12, 2008, pp. 5118-5128. [8] Y. Zhang, D. Lukas, et al. “Improvements on Ant Routing for Sensor Networks,” Lecture Notes in Computer Science, 2004, pp.154-165. [9] K. Zeng, W. J. Lou, et al. “On End-to-end Throughput of Opportunistic Routing in Multi-Rate and Multi-Hop Wireless Networks,” Proceedings of the IEEE INFOCOM, Phoenix, 2008, pp. 1490-1498. [10] J. N. Laneman and G. Wornell “Energy-Efficient Antenna Sharing and Relaying for Wireless Networks,” Proceeding of IEEE Wireless Communications and Networking. Chicago, 2000, pp.7-12. [11] T. Camilo, C. Carreto, et al. “An Energy-Efficient Ant- Based Routing Algorithm for Wireless Sensor Networks,” Ant Colony Optimization and Swarm Intelligence, 2006, pp. 49-59. [12] J. Li and P. Mohapatra “Analytical Modeling and Mitigation Techniques for the Energy Hole Problems in Sensor Networks,” Pervasive and Mobile Computing, Vol. 3, 2007, pp.233-254. [13] V. Lakshmi, Thanayankizil, Aravind Kailas, et al. “Two Energy-Saving Schemes for Cooperative Transmission with Opportunistic Large Arrays,” Proceedings of Global Telecommunications Conference, Washington, DC, 2007, pp.1038-1042. [14] S. Okdem and D. Karaboga. “Routing in Wireless Sensor Networks Using Ant Colony Optimization,” Proceedings of Adaptive Hardware and Systems, Istanbul, 2006, pp. 401-404. [15] M. Dorigo and V. Maniezzo Etal, “The Ant System: Optimization by a Colony of Cooperating Agents,” IEEE Transaction on Systems, Man, and Cybernetics - Part B, Vol.26, No. 1, 1996, pp. 1-13. [16] A. Orda and R. Rom, “Shortest-Path and Minimum-Delay Algorithms in Networks with Time-Dependent Edge- Length,” Vol. 37, No. 3, 1990, pp. 607-625. [17] M. R. Garey and D. S. Johnson, “Computers and Intractability: a Guide to the Theory of NP Completeness,” Whfreemanand Company, New York, 1979.