This Article 
 Bibliographic References 
 Add to: 
Greedy Routing with Anti-Void Traversal for Wireless Sensor Networks
July 2009 (vol. 8 no. 7)
pp. 910-922
Wen-Jiunn Liu, National Chiao Tung University, Hsinchu
Kai-Ten Feng, National Chiao Tung University, Hsinchu
The unreachability problem (i.e., the so-called void problem) that exists in the greedy routing algorithms has been studied for the wireless sensor networks. Some of the current research work cannot fully resolve the void problem, while there exist other schemes that can guarantee the delivery of packets with the excessive consumption of control overheads. In this paper, a greedy anti-void routing (GAR) protocol is proposed to solve the void problem with increased routing efficiency by exploiting the boundary finding technique for the unit disk graph (UDG). The proposed rolling-ball UDG boundary traversal (RUT) is employed to completely guarantee the delivery of packets from the source to the destination node under the UDG network. The boundary map (BM) and the indirect map searching (IMS) scheme are proposed as efficient algorithms for the realization of the RUT technique. Moreover, the hop count reduction (HCR) scheme is utilized as a short-cutting technique to reduce the routing hops by listening to the neighbor's traffic, while the intersection navigation (IN) mechanism is proposed to obtain the best rolling direction for boundary traversal with the adoption of shortest path criterion. In order to maintain the network requirement of the proposed RUT scheme under the non-UDG networks, the partial UDG construction (PUC) mechanism is proposed to transform the non-UDG into UDG setting for a portion of nodes that facilitate boundary traversal. These three schemes are incorporated within the GAR protocol to further enhance the routing performance with reduced communication overhead. The proofs of correctness for the GAR scheme are also given in this paper. Comparing with the existing localized routing algorithms, the simulation results show that the proposed GAR-based protocols can provide better routing efficiency.

[1] D. Estrin, R. Govindan, J. Heidemann, and S. Kumar, “Next Century Challenges: Scalable Coordination in Sensor Networks,” Proc. ACM MobiCom, pp. 263-270, Aug. 1999.
[2] G.G. Finn, “Routing and Addressing Problems in Large Metropolitan-Scale Internetworks,” Technical Report ISI/RR-87-180, Information Sciences Inst., Mar. 1987.
[3] B. Karp and H.T. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks,” Proc. ACM MobiCom, pp.243-254, Aug. 2000.
[4] I. Stojmenović and X. Lin, “Loop-Free Hybrid Single-Path/Flooding Routing Algorithms with Guaranteed Delivery for Wireless Networks,” IEEE Trans. Parallel and Distributed Systems, vol. 12, no. 10, pp. 1023-1032, Oct. 2001.
[5] R. Jain, A. Puri, and R. Sengupta, “Geographical Routing Using Partial Information for Wireless Ad Hoc Networks,” IEEE Personal Comm. Magazine, vol. 8, no. 1, pp. 48-57, Feb. 2001.
[6] D. Chen and P.K. Varshney, “On-Demand Geographic Forwarding for Data Delivery in Wireless Sensor Networks,” Elsevier Computer Comm., vol. 30, no. 14-15, pp. 2954-2967, Oct. 2007.
[7] I. Stojmenović, M. Russell, and B. Vukojevic, “Depth First Search and Location Based Localized Routing and QoS Routing in Wireless Networks,” Proc. IEEE Int'l Conf. Parallel Processing (ICPP '00), pp. 173-180, Aug. 2000.
[8] T. He, J.A. Stankovic, C. Lu, and T. Abdelzaher, “SPEED: A Stateless Protocol for Real-Time Communication in Sensor Networks,” Proc. Int'l Conf. Distributed Computing Systems (ICDCS '03), pp. 46-55, May 2003.
[9] V.C. Giruka and M. Singhal, “Angular Routing Protocol for Mobile Ad Hoc Networks,” Proc. IEEE Int'l Conf. Distributed Computing Systems Workshops (ICDCSW '05), pp. 551-557, June 2005.
[10] W.J. Liu and K.T. Feng, “Largest Forwarding Region Routing Protocol for Mobile Ad Hoc Networks,” Proc. IEEE Global Comm. Conf. (GLOBECOM '06), pp. 1-5, Nov. 2006.
[11] L. Zou, M. Lu, and Z. Xiong, “A Distributed Algorithm for the Dead End Problem of Location Based Routing in Sensor Networks,” IEEE Trans. Vehicular Technology, vol. 54, no. 4, pp.1509-1522, July 2005.
[12] N. Arad and Y. Shavitt, “Minimizing Recovery State in Geographic Ad-Hoc Routing,” Proc. ACM MobiHoc '06, pp.13-24, May 2006.
[13] S. Chen, G. Fan, and J.H. Cui, “Avoid “Void” in Geographic Routing for Data Aggregation in Sensor Networks,” Int'l J. Ad Hoc and Ubiquitous Computing, vol. 1, no. 4, pp. 169-178, 2006.
[14] D.D. Couto and R. Morris, “Location Proxies and Intermediate Node Forwarding for Practical Geographic Forwarding,” Technical Report MIT-LCS-TR-824, MIT Laboratory for Computer Science, June 2001.
[15] J. Na, D. Soroker, and C.K. Kim, “Greedy Geographic Routing Using Dynamic Potential Field for Wireless Ad Hoc Networks,” IEEE Comm. Letters, vol. 11, no. 3, pp. 243-245, Mar. 2007.
[16] H. Frey and I. Stojmenović, “On Delivery Guarantees of Face and Combined Greedy Face Routing in Ad Hoc and Sensor Networks,” Proc. ACM MobiCom '06, pp. 390-401, Sept. 2006.
[17] P. Bose, P. Morin, I. Stojmenović, and J. Urrutia, “Routing with Guaranteed Delivery in Ad Hoc Wireless Networks,” ACM/Kluwer Wireless Networks, vol. 7, no. 6, pp. 609-616, Nov. 2001.
[18] E. Kranakis, H. Singh, and J. Urrutia, “Compass Routing on Geometric Networks,” Proc. Canadian Conf. Computational Geometry (CCCG '99), pp. 51-54, Aug. 1999.
[19] F. Kuhn, R. Wattenhofer, and A. Zollinger, “Asymptotically Optimal Geometric Mobile Ad-Hoc Routing,” Proc. Int'l Workshop Discrete Algorithms and Methods for Mobile Computing and Comm. (Dial-M '02), pp. 24-33, Sept. 2002.
[20] F. Kuhn, R. Wattenhofer, and A. Zollinger, “Worst-Case Optimal and Average-Case Efficient Geometric Ad-Hoc Routing,” Proc. ACM MobiHoc '03, pp. 267-278, June 2003.
[21] F. Kuhn, R. Wattenhofer, Y. Zhang, and A. Zollinger, “Geometric Ad-Hoc Routing: Of Theory and Practice,” Proc. ACM Symp. Principles of Distributed Computing (PODC '03), pp. 63-72, July 2003.
[22] B. Leong, S. Mitra, and B. Liskov, “Path Vector Face Routing: Geographic Routing with Local Face Information,” Proc. IEEE Int'l Conf. Network Protocols (ICNP '05), pp. 147-158, Nov. 2005.
[23] Q. Fang, J. Gao, and L. Guibas, “Locating and Bypassing Routing Holes in Sensor Networks,” Proc. IEEE INFOCOM '04, pp. 2458-2468, Mar. 2004.
[24] D.B. West, Introduction to Graph Theory, second ed. Prentice Hall, 2000.
[25] K.R. Gabriel and R.R. Sokal, “A New Statistical Approach to Geographic Variation Analysis,” Systematic Zoology, vol. 18, no. 3, pp. 259-278, Sept. 1969.
[26] G.T. Toussaint, “The Relative Neighborhood Graph of a Finite Planar Set,” Pattern Recognition, vol. 12, no. 4, pp. 261-268, 1980.
[27] Y.J. Kim, R. Govindan, B. Karp, and S. Shenker, “On the Pitfalls of Geographic Face Routing,” Proc. ACM/SIGMOBILE Joint Workshop Foundations of Mobile Computing (DIALM-POMC '05), pp. 34-43, Sept. 2005.
[28] S. Datta, I. Stojmenović, and J. Wu, “Internal Node and Shortcut Based Routing with Guaranteed Delivery in Wireless Networks,” Kluwer Cluster Computing, vol. 5, no. 2, pp. 169-178, 2002.
[29] V.C. Giruka and M. Singhal, “Hello Protocols for Ad-Hoc Networks: Overhead and Accuracy Tradeoffs,” Proc. IEEE Int'l Symp. World of Wireless, Mobile and Multimedia Networks (WoWMoM '05), pp. 354-361, June 2005.
[30] E. Horowitz, S. Sahni, and D. Mehta, Fundamentals of Data Structures in C++, second ed. Silicon Press, 2006.
[31] J. Heidemann, N. Bulusu, J. Elson, C. Intanagonwiwak, K. Lan, Y. Xu, W. Ye, D. Estrin, and R. Govindan, “Effects of Detail in Wireless Network Simulation,” Proc. SCS Multiconf. Distributed Simulation, pp. 3-11, Jan. 2001.

Index Terms:
Greedy routing, void problem, unit disk graph, localized algorithm, wireless sensor network.
Wen-Jiunn Liu, Kai-Ten Feng, "Greedy Routing with Anti-Void Traversal for Wireless Sensor Networks," IEEE Transactions on Mobile Computing, vol. 8, no. 7, pp. 910-922, July 2009, doi:10.1109/TMC.2008.162
Usage of this product signifies your acceptance of the Terms of Use.