This Article 
 Bibliographic References 
 Add to: 
A Mobile-Directory Approach to Service Discovery in Wireless Ad Hoc Networks
October 2008 (vol. 7 no. 10)
pp. 1242-1256
We present the Service Directory Placement Algorithm (SDPA), a directory-placement scheme that leverages the performance of existing service discovery protocols over wireless ad-hoc networks. SDPA promotes the deployment of a nomadic service directory, whose current location in the network varies according to the dynamics of service-discovery queries driven by the users' applications and partial knowledge of the network?s topology. SDPA is based on a heuristic approach, whose performance is optimized by formulating the directory-placement problem as a Semi-Markov Decision Process solved by means of a reinforcement-learning technique known as Q-Learning. Performance evaluations obtained through computer simulations of networks with up to 45 hosts moving at pedestrian walking speeds equal to or slower than 2 m/s reveal average bandwidth savings close to 50% over a default broadcast approach for service discovery once an efficient directory-placement policy is found.

[1] D. Cavalcanti et al., “Issues in Integrating Cellular Networks WLANs, AND MANETs: A Futuristic Heterogeneous Wireless Network,” IEEE Wireless Comm., vol. 12, no. 3, June 2005.
[2] C.R. Dow et al., “A Study of Recent Research Trends and Experimental Guidelines in Mobile Ad-Hoc Network,” Proc. 19th Int'l IEEE Conf. Advanced Information Networking and Applications (AINA '05), Mar. 2005.
[3] Y. Tseng, Y. Li, and Y. Chang, “On Route Lifetime in Multihop Mobile Ad Hoc Networks,” IEEE Trans. Mobile Computing, vol. 2, no. 4, Oct.-Dec. 2003.
[4] X. Hong, K. Xu, and M. Gerla, “Scalable Routing Protocols for Mobile Ad Hoc Networks,” IEEE Network, July-Aug. 2002.
[5] D. Kim et al., “Analysis of the Interaction between TCP Variants and Routing Protocols in MANETs,” Proc. Int'l IEEE Conf. Parallel Processing Workshops (ICPPW), 2005.
[6] S. Xu and T. Saadawi, “Does the IEEE 802.11 MAC Protocol Work Well in Multihop Wireless Ad Hoc Networks,” IEEE Comm. Magazine, June 2000.
[7] L.M. Feeney, “An Energy Consumption Model for Performance Analysis of Routing Protocols for Mobile Ad-Hoc Networks,” J. Mobile Networks and Applications, Kluwer Academic Publishers, 2001.
[8] Z. Qing and L. Tong, “Energy Efficiency of Large-Scale Wireless Networks: Proactive versus Reactive Networking,” IEEE J. Selected Areas in Comm., vol. 23, no. 5, May 2005.
[9] P. Wei and L. Xi-Cheng, “On the Reduction of Broadcast Redundancy in Mobile Ad Hoc Networks,” Proc. Mobile and Ad Hoc Networking and Computing, Aug. 2000.
[10] S. Gonzalez-Valenzuela, S. Vuong, and V.C.M. Leung, “A Reinforcement-Learning Approach to Service Directory Placement in Wireless Ad-Hoc Networks,” Proc. Fifth IEEE Workshop Applications and Services in Wireless Networks, June-July 2005.
[11] R. Handorean and G.-C. Roman, “Service Provision in Ad Hoc Networks,” Proc. Fifth Int'l Conf. Coordination Models and Languages (Coordination '02), F. Arbab and C. Talcott, eds., Apr. 2002.
[12] U.C. Kozat and L. Tassiulas, “Service Discovery in Mobile Ad-Hoc Networks: An Overall Perspective on Architectural Choices and Network Later Support Issues,” Ad-Hoc Networks, Elsevier Science, 2004.
[13] Jini Network Technology,, 2008.
[14] Service Location Protocol v2, IETF RFC 2608, , 2008.
[15] G. Cornuejols, G.L. Nemhauser, and L.A. Wolsey, “The Uncapacitated Facility Location Problem,” Discrete Location Theory, P. Mirchandani and R. Francis, eds., pp. 119-171, John Wiley & Sons, 1990.
[16] V. Arya et al., “Local Search Heuristics for k-Median and Facility Location Problems,” SIAM J. Computing, vol. 33, no. 3, 2004.
[17] C. Papadimitriou, “Worst-Case and Probabilistic Analysis of a Geometric Location Problem,” SIAM J. Computing, vol. 10, no. 3, 1981.
[18] L. Qiu, V.N. Padmanabhan, and G.M. Voelker, “On the Placement of Web Server Replicas,” Proc. IEEE INFOCOM '01, Apr. 2001.
[19] B. Li et al., “On the Optimal Placement of Web Proxies in the Internet,” Proc. IEEE INFOCOM '99, pp. 1282-1290, Mar. 1999.
[20] D. Chakraborty, A. Joshi, Y. Yesha, and T. Finin, “Toward Distributed Service Discovery in Pervasive Computing Environments,” IEEE Trans. Mobile Computing, vol. 5, no. 2, pp. 97-112, Feb. 2006.
[21] V. Lenders, M. May, and B. Plattner, “Service Discovery in Mobile Ad Hoc Networks: A Field Theoretic Approach,” J. Pervasive and Mobile Computing, vol. 1, no. 3, pp. 343-370, Sept. 2005.
[22] M.J. Kima, M. Kumara, and B.A. Shirazib, “Service Discovery Using Volunteer Nodes in Heterogeneous Pervasive Computing Environments,” J. Pervasive and Mobile Computing, vol. 2, pp. 313-343, 2006.
[23] F. Yu, V.W.S. Wong, and V.C.M. Leung, “Efficient QoS Provisioning for Adaptive Multimedia in Mobile Communication Networks by Reinforcement Learning,” ACM/Springer J. Mobile Networks and Applications, vol. 11, no. 1, pp. 101-110, Feb. 2006.
[24] C.K. Tham and J.C. Renaud, “Multi-Agent Systems on Sensor Networks: A Distributed Reinforcement Learning Approach,” Proc. Second Int'l Conf. Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP '05), Dec. 2005.
[25] T. Camp, J. Boleng, and V. Davies, “A Survey of Mobility Models for Ad Hoc Network Research,” Wireless Communication and Mobile Computing, special issue on mobile ad hoc networking research, trends and applications, vol. 2, no. 5, pp. 483-502, 2002.
[26] C. Bettstetter, G. Resta, and P. Santi, “The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks,” IEEE Trans. Mobile Computing, vol. 2, no. 3, July-Sept. 2003.
[27] F. Bai, N. Sadagopan, and A. Helmy, “IMPORTANT: A Framework to Systematically Analyze the Impact of Mobility on Performance of RouTing Protocols for Adhoc NeTworks,” Proc. IEEE INFOCOM, 2003.
[28] X. Hong, M. Gerla, G. Pei, and C.-C. Chiang, “A Group Mobility Model for Ad Hoc Wireless Networks,” Proc. ACM/IEEE Int'l Symp. Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM '99), Aug. 1999.
[29] G. Lin, G. Noubir, and R. Rajaraman, “Mobility Models for Ad Hoc Network Simulation,” Proc. IEEE INFOCOM '04, Mar. 2004.
[30] M.L. Puterman, “Markov Decision Processes,” Wiley Interscience, 1994.
[31] R.S. Sutton and A.G. Barto, Reinforcement Learning—An Introduction. MIT Press, 1998.
[32] C.J.C.H. Watkins, “Learning from Delayed Rewards,” PhD dissertation, Cambridge Univ., 1989.
[33] S.J. Bradtke and M.O. Duff, “Reinforcement Learning Methods for Continuous-Time Markov Decision Problems,” Advances in Neural Information Processing Systems 7, G. Tesauro, D.S. Touretzky, and T.K. Leen, eds., 1995.
[34] The OMNeT++ Discrete Event Simulator Environment, http:/, 2008.
[35] D. Johnson and D. Maltz, “Dynamic Source Routing in Ad Hoc Wireless Networks,” Mobile Computing, Imielinski and Korth, eds., Kluwer Academic Publishers, 1996.
[36] C. Perkins, E. Belding-Royer, and S. Das, Ad-Hoc On-Demand Distance Vector (AODV) Routing, IETF RFC 3561, July 2003.
[37] J. Yoon, M. Liu, and B. Noble, “Random Waypoint Considered Harmful,” Proc. IEEE INFOCOM '03, Apr. 2003.
[38] Bluetooth Special Interest Group Specification, Version 1.2, http:/, 2008.

Index Terms:
Machine learning, Mobile communication systems, Algorithm/protocol design and analysis, Data communications, Ubiquitous computing
Sergio González-Valenzuela, Son T. Vuong, Victor C.M. Leung, "A Mobile-Directory Approach to Service Discovery in Wireless Ad Hoc Networks," IEEE Transactions on Mobile Computing, vol. 7, no. 10, pp. 1242-1256, Oct. 2008, doi:10.1109/TMC.2008.26
Usage of this product signifies your acceptance of the Terms of Use.