Distributed Distance Sensitive iMesh Based Service Discovery in Dense WSAN
We investigated performance of localized distance-sensitive service discovery algorithm iMesh, which generates information structure in static network, to store the information about nearby actors (service providers). In a network with grid structure, this is achieved by advertising service provider positions in four geographical directions. The propagation of information about remote service providers is restricted by a blocking rule, to reduce the message overhead and provide distance sensitivity. A node requiring service (service consumer) conducts lookup process to obtain information about nearby service providers from the iMesh structure. We modified iMesh to enable its use in dense networks with topologies other than grid by introducing iMesh areas instead of iMesh edges. Our simulations compare performance of modified iMesh with another localized service discovery scheme (quorum) in dense networks with random topologies. We show that iMesh finds the nearest service provider in >95% of cases. It significantly decreases the message overhead compared to quorum, without compromising quality of service discovery.
Keywordsservice discovery localized algorithm wireless sensor and actor networks iMesh
Unable to display preview. Download preview PDF.
- 2.Stojmenovic, I., Liu, D., Jia, X.: A scalable quorum based location service in ad hoc and sensor networks. International Journal of Communication Networks and Distributed Systems 1(1) (2008) (invited paper)Google Scholar
- 3.Nayak, A., Stojmenovic, I.: Wireless Sensor and Actuator Networks - Algorithms and Protocols for Scalable Coordination and Data Communication. John Wiley & Sons, ISBN-13: 978-0-470-17082-3Google Scholar
- 7.Aydin, I., Shen, C.C.: Facilitating match-making service in ad hoc and sensor networks using pseudo quorum. In: IEEE ICCCN (2002)Google Scholar
- 10.Li, J., Jannotti, J., Couto, D.S.J.D., Karger, D.R., Morris, R.: A Scalable Location Service for Geographic Ad Hoc Routing. In: Proc. ACM MobiCom, pp. 120–130 (2000)Google Scholar
- 11.Ratnasamy, S., Karp, B., Yin, L., Yu, F.: GHT: A Geographic Hash Table for Data-Centric Storage. In: Proc. Intl Workshop on Wireless Sensor Networks and Applications, WSNA, pp. 78–87 (2002)Google Scholar
- 12.Tchakarov, J.B., Vaidya, N.H.: Efficient Content Location in Wireless Ad Hoc Networks. In: Proc. IEEE Intl Conf. Mobile Data Management, MDM, pp. 74–85 (2004)Google Scholar
- 13.Fang, Q., Gao, J., Guibas, L.J.: Landmark-Based Information Storage and Retrieval in Sensor Networks. In: Proc. IEEE INFOCOM, pp. 286–297 (2006)Google Scholar