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Adaptive Quality-Aware Replication in Wireless Sensor Networks

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 56))

Abstract

Typical sensor network deployments are usually built for long-term usage. Additionally, the sensor nodes are often exposed to harsh environmental influences. Due to these constraints, it is mandatory for applications to be able to compensate the failure of nodes. Providing a persistent storage even in the presence of failing nodes demands for replication within the sensor network. However, recent work in the field of replication in sensor networks often does not consider the suitability of the sensor nodes to store replicas in terms of e.g. available storage, energy or connectivity. In this paper, we envision an adaptive quality-aware replication scheme which enables the storage of replicas based on a scoring system reflecting the suitability of a replica node. Furthermore, we propose an adaptable data migration strategy using a weighting function to achieve an adequate placement for the replicas. A resilient storage strategy enables the survival of replicas after migration despite unpredictable node failures. We expect that our replication scheme highly increases the availability of sensor network data despite of node failures and network partitioning requiring only a small number of replicas within the network.

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References

  1. Aly, M., Chrysanthis, P.K., Pruhs, K.: Decomposing data-centric storage query hot-spots in sensor networks. In: Annual International Conference on Mobile and Ubiquitous Systems, pp. 1–9 (2006)

    Google Scholar 

  2. Aly, S.A., Kong, Z., Soljanin, E.: Fountain codes based distributed storage algorithms for large-scale wireless sensor networks. In: IPSN, pp.171–182 (2008)

    Google Scholar 

  3. Apaydin, T., Vural, S., Sinha, P.: On improving data accessibility in storage based sensor networks. IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 1–9 (2007)

    Google Scholar 

  4. Diao, Y., Ganesan, D., Mathur, G., Shenoy, P.J.: Rethinking data management for storage-centric sensor networks. In: CIDR, pp. 22–31 (2007), http://www.crdrdb.org

  5. Gil, T.M., Madden, S.: Scoop: An adaptive indexing scheme for stored data in sensor networks. In: International Conference on Data Engineering, pp. 1345–1349 (2007)

    Google Scholar 

  6. Kamra, A., Misra, V., Feldman, J., Rubenstein, D.: Growth codes: maximizing sensor network data persistence, pp. 255–266 (2006)

    Google Scholar 

  7. Kroeller, A., Pfisterer, D., Buschmann, C., Fekete, S., Fischer, S.: Shawn: A new approach to simulating wireless sensor networks. In: Design, Analysis, and Simulation of Distributed Systems, Part of the SpringSim (2005)

    Google Scholar 

  8. Li, R.G.X., Bian, F., Hong, W.: Rebalancing distributed data storage in sensor networks. Techincal Report USC-CS-05-852 (2005)

    Google Scholar 

  9. Lin, Y., Li, B., Liang, B.: Differentiated data persistence with priority random linear codes, p. 47 (2007)

    Google Scholar 

  10. Madden, S.R., Franklin, M.J., Hellerstein, J.M., Hong, W.: Tinydb: an acquisitional query processing system for sensor networks. ACM Trans. Database Syst. 30(1), 122–173 (2005)

    Article  Google Scholar 

  11. Newsome, J., Song, D.: Gem: Graph embedding for routing and data-centric storage in sensor networks without geographic information. In: SenSys 2003: Proceedings of the 1st international conference on Embedded networked sensor systems, pp. 76–88. ACM Press, New York (2003)

    Chapter  Google Scholar 

  12. Piotrowski, K., Langendoerfer, P., Peter, S.: tinydsm: A highly reliable cooperative data storage for wireless sensor networks. In: International Symposium on Collaborative Technologies and Systems, pp. 225–232 (2009)

    Google Scholar 

  13. Ratnasamy, S., Karp, B., Yin, L., Yu, F., Estrin, D., Govindan, R., Shenker, S.: Ght: a geographic hash table for data-centric storage. In: WSNA 2002: Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications, pp. 78–87. ACM, New York (2002)

    Chapter  Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Neumann, J., Reinke, C., Hoeller, N., Linnemann, V. (2009). Adaptive Quality-Aware Replication in Wireless Sensor Networks. In: Ślęzak, D., Kim, Th., Chang, A.CC., Vasilakos, T., Li, M., Sakurai, K. (eds) Communication and Networking. FGCN 2009. Communications in Computer and Information Science, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10844-0_48

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  • DOI: https://doi.org/10.1007/978-3-642-10844-0_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10843-3

  • Online ISBN: 978-3-642-10844-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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