• Publication
  • 2010
  • Issue No. 6 - June
  • Abstract - QELAR: A Machine-Learning-Based Adaptive Routing Protocol for Energy-Efficient and Lifetime-Extended Underwater Sensor Networks
 This Article 
 Bibliographic References 
 Add to: 
QELAR: A Machine-Learning-Based Adaptive Routing Protocol for Energy-Efficient and Lifetime-Extended Underwater Sensor Networks
June 2010 (vol. 9 no. 6)
pp. 796-809
Tiansi Hu, University of Connecticut, Storrs
Yunsi Fei, University of Connecticut, Storrs
Underwater sensor network (UWSN) has emerged in recent years as a promising networking technique for various aquatic applications. Due to specific characteristics of UWSNs, such as high latency, low bandwidth, and high energy consumption, it is challenging to build networking protocols for UWSNs. In this paper, we focus on addressing the routing issue in UWSNs. We propose an adaptive, energy-efficient, and lifetime-aware routing protocol based on reinforcement learning, QELAR. Our protocol assumes generic MAC protocols and aims at prolonging the lifetime of networks by making residual energy of sensor nodes more evenly distributed. The residual energy of each node as well as the energy distribution among a group of nodes is factored in throughout the routing process to calculate the reward function, which aids in selecting the adequate forwarders for packets. We have performed extensive simulations of the proposed protocol on the Aqua-sim platform and compared with one existing routing protocol (VBF) in terms of packet delivery rate, energy efficiency, latency, and lifetime. The results show that QELAR yields 20 percent longer lifetime on average than VBF.

[1] I.F. Akyildiz, D. Pompili, and T. Melodia, "State of the Art in Protocol Research for Underwater Acoustic Sensor Networks," Proc. SIGMOBILE Mobile Computing Comm. Rev., vol. 11, no. 4, pp. 11-22, 2007.
[2] G. Acar and A.E. Adams, "ACMENet: An Underwater Acoustic Sensor Network for Real-Time Environmental Monitoring in Coastal Areas," IEE Proc. Radar, Sonar, and Navigation, vol. 153, pp. 365-380, 2006.
[3] J. Rice, "Acoustic Communication and Navigation Networks," Proc. Int'l Conf. Underwater Acoustic Measurements: Technologies & Results, July 2005.
[4] L. Freitag, M. Grund, C. von Alt, R. Stokey, and T. Austin, "A Shallow Water Acoustic Network for Mine Countermeasures Operations with Autonomous Underwater Vehicles," Underwater Defense Technology, 2005.
[5] J. Heidemann, Y. Li, A. Syed, J. Wills, and W. Ye, "Research Challenges and Applications for Underwater Sensor Networking," Proc. IEEE Wireless Comm. & Networking Conf., Apr. 2006.
[6] L. Freitag, M. Grund, S. Singh, J. Partan, P. Koski, and K. Ball, "The WHOI Micro-Modem: An Acoustic Communications and Navigation System for Multiple Platforms," Proc. IEEE Oceans, 2005.
[7] Crossbow Inc., Mica2 Data Sheet, http://www.xbow.com/ products/Product_pdf_files/ Wireless_pdfMICA2_Datasheet. pdf , 2008.
[8] Y. Chen and Q. Zhao, "On the Lifetime of Wireless Sensor Networks," IEEE Comm. Letters, vol. 9, no. 11, pp. 976-978, Nov. 2005.
[9] S. Lee, B. Bhattacharjee, and S. Banerjee, "Efficient Geographic Routing in Multihop Wireless Networks," Proc. Int'l Symp. Mobile Ad Hoc Networking & Computing, pp. 230-241, 2005.
[10] C. Ma and Y. Yang, "Battery-Aware Routing for Streaming Data Transmissions in Wireless Sensor Networks," Mobile Networks and Applications, vol. 11, no. 5, pp. 757-767, 2006.
[11] J.-H. Chang and L. Tassiulas, "Fast Approximate Algorithms for Maximum Lifetime Routing in Wireless Ad-Hoc Networks," Proc. Int'l Conf. Broadband Comm., High Performance Networking, and Performance of Comm. Networks, pp. 702-713, 2000.
[12] J.-H. Chang and R. Tassiulas, "Energy Conserving Routing in Wireless Ad-Hoc Networks," Proc. IEEE INFOCOM, pp. 22-31, 2000.
[13] A. Sankar and Z. Liu, "Maximum Lifetime Routing in Wireless Ad-Hoc Networks," Proc. IEEE INFOCOM, pp. 1089-1097, 2004.
[14] Y. Cui, Y. Xue, and K. Nahrstedt, "A Utility-Based Distributed Maximum Lifetime Routing Algorithm for Wireless Networks," Trans. Vehicular Technology, special issue on cross-layer design in mobile ad hoc networks & wireless sensor networks, vol. 55, pp. 797-805, May 2006.
[15] P. Xie, J.-H. Cui, and L. Lao, "VBF: Vector-Based Forwarding Protocol for Underwater Sensor Networks," Proc. Networking, pp. 1216-1221, 2006.
[16] L. Zhang, T.-H. Kim, and C. Liu, M.-T. Sun, and A. Lim, "Traffic-Aware Routing Tree for Underwater 3D Geographic Routing," Proc. Int'l Conf. Intelligent Sensors, Sensor Networks, and Information Processing, pp. 487-492, Dec. 2008.
[17] H. Yan, J. Shi, and J.-H. Cui, "DBR: Depth-Based Routing for Underwater Sensor Networks," Proc. Networking, pp. 72-86, 2008.
[18] C.-H. Yang and K.-F. Ssu, "An Energy-Efficient Routing Protocol in Underwater Sensor Networks," Proc. Int'l Conf. Sensing Technology, pp. 114-118, Dec. 2008.
[19] D. Pompili, T. Melodia, and I.F. Akyildiz, "A Resilient Routing Algorithm for Long-Term Applications in Underwater Sensor Networks," Proc. Mediterranean Ad Hoc Networking Workshop, 2006.
[20] J.M. Jornet, M. Stojanovic, and M. Zorzi, "Focused Beam Routing Protocol for Underwater Acoustic Networks," Proc. ACM Int'l Workshop Underwater Networks, pp. 75-82, Sept. 2008.
[21] J.A. Boyan and M.L. Littman, "Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach," Proc. Advances in Neural Information Processing Systems, vol. 6, pp. 671-678, 1994.
[22] S. Kumar and R. Miikkulainen, "Dual Reinforcement Q-Routing: An On-Line Adaptive Routing Algorithm," Proc. Artificial Neural Networks in Eng. Conf., 1997.
[23] P. Wang and T. Wang, "Adaptive Routing for Sensor Networks Using Reinforcement Learning," Proc. IEEE Int'l Conf. Computer and Information Technology, p. 219, 2006.
[24] G.D. Caro and M. Dorigo, "Ant Colonies for Adaptive Routing in Packet-Switched Communications Networks," Proc. Fifth Int'l Conf. Parallel Problem Solving from Nature, pp. 673-682, 1998.
[25] M. Güneş, U. Sorges, and I. Bouazizi, "ARA—The Ant-Colony Based Routing Algorithm for MANETs," Proc. Int'l Conf. Parallel Processing Workshop, Aug. 2002.
[26] S. Kamali and J. Opatrny, "A Position Based Ant Colony Routing Algorithm for Mobile Ad-Hoc Networks." J. Networks, vol. 3, no. 4, pp. 31-41, 2008.
[27] J.-H. Cui, J. Kong, M. Gerla, and S. Zhou, "Challenges: Building Scalable Mobile Underwater Wireless Sensor Networks for Aquatic Applications," Proc. IEEE Network, special issue on wireless sensor networking, pp. 12-18, 2006.
[28] R.S. Sutton and A.G. Barto, Reinforcement Learning: An Introduction. The MIT Press, Mar. 1998.
[29] S. McCanne and S. Floyd, ns-Network Simulator, http:// www-mash.cs.berkeley.edu ns/, 2008.

Index Terms:
Routing protocols, distributed networks, wireless communication, mobile communication systems.
Tiansi Hu, Yunsi Fei, "QELAR: A Machine-Learning-Based Adaptive Routing Protocol for Energy-Efficient and Lifetime-Extended Underwater Sensor Networks," IEEE Transactions on Mobile Computing, vol. 9, no. 6, pp. 796-809, June 2010, doi:10.1109/TMC.2010.28
Usage of this product signifies your acceptance of the Terms of Use.