A data-centric storage scheme for high storage utilization in wireless sensor networks
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Abstract
In wireless sensor networks, a data-centric storage (DCS) scheme is one of representative researches to store sensor readings and to process a query efficiently. The DCS scheme assigns distributed data regions to sensor nodes and stores sensor readings to the sensor node which is responsible for the data region to process the query efficiently. However, the existing DCS schemes have some drawbacks that the sensor nodes have the fixed ranges to store sensor readings. Because the ranges of the sensor readings change periodically in real world applications, the existing DCS schemes have problems that they use storage space unevenly in entire sensors and their network lifetimes are reduced. To overcome this problem, we propose a novel DCS scheme for high storage utilization in wireless sensor networks. The proposed scheme stores the sensed data equally in the entire sensor network to improve the storage utilization. To show the superiority of our proposed scheme, we compare it with the existing DCS schemes. Our experimental results show that our proposed scheme improves about 498 % storage utilization and about 377.7 % network lifetime over the existing schemes on average.
Keywords
Wireless sensor networks Data-centric storage In-network query processing Context-aware Storage utilizationNotes
Acknowledgments
This research was supported by the Ministry of Science, ICT and Future Planning (MSIP), Korea, under the Information Technology Research Center (ITRC) support program (NIPA-2013-H0301-13-4009) supervised by the National IT Industry Promotion Agency (NIPA), the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIP) (No. 2013R1A2A2A01015710), and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education(2012R1A1A2A10042015).
References
- 1.Damdinsuren, C., Kominami, D., Sugano, M., Murata, M., Hatauchi, T.: Lifetime extension based on residual energy for receiver-driven multi-hop wireless network. Clust. Comput. 16(3), 469–480 (2013)CrossRefGoogle Scholar
- 2.Liu, L., Hu, B., Li, L.: Algorithms for energy efficient mobile object tracking in wireless sensor networks. Clust. Comput. 13(2), 181–197 (2010)CrossRefGoogle Scholar
- 3.Culler, D., Estrin, D., Srivastava, M.: Guest editors’ introduction: overview of sensor networks. IEEE Comput. 37(8), 41–49 (2004)CrossRefGoogle Scholar
- 4.Stankovic, J.A.: Wireless sensor networks. IEEE Comput. 41(10), 92–95 (2008)CrossRefGoogle Scholar
- 5.Web Exclusive. Industrial Wireless Sensor Networks: trends and developments. http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=90824 (2012). Accessed 1 Nov 2013
- 6.Park, C., Kim, H., Jung, I.: Traffic-aware routing protocol for wireless sensor networks. Clust. Comput. 15(1), 27–36 (2012)CrossRefMathSciNetGoogle Scholar
- 7.Dhurandher, S.K., Misra, S., Mittal, H., Agarwal, A., Woungang, I.: Agents for congestion control in ad hoc wireless sensor networks. Clust. Comput. 14(1), 41–53 (2011)CrossRefGoogle Scholar
- 8.Torkestani, J.A., Meybodi, M.R.: A mobility-based cluster formation algorithm for wireless mobile ad hoc networks. Clust. Comput. 14(4), 311–324 (2011)CrossRefGoogle Scholar
- 9.Cerpa, A., Elson, J., Estrin, D., Girod, L., Hamilton, M., Zhao, J.: Habitat monitoring: application driver for wireless communications technology. In: ACM Workshop on Data Communications in Latin America and the Caribbean, pp. 20–41 (2001)Google Scholar
- 10.Szewczyk, R., Osterweil, E., Polastre, J., Hamilton, M., Mainwaring, A., Estrin, D.: Habitat monitoring with sensor networks. Commun. ACM 47(6), 34–40 (2004)CrossRefGoogle Scholar
- 11.Ratnasamy, S., Karp, B., Shenker, S., Estrin, D., Govindan, R., Yin, L., Yu, F.: Data-centric storage in sensornets with GHT, a geographic hash table. Mob. Netw. Appl. 8(4), 427–442 (2003)CrossRefGoogle Scholar
- 12.Aly, M., Chrysanthis, P.K., Pruths, K.: Decomposing data-centric storage query hot-spot in sensor networks. In: Annual International Conference on Mobile and Ubiquitous Systems, pp. 1–9 (2006)Google Scholar
- 13.Li, X., Kim, Y., Govindan, R., Hon, W.: Multi-dimensional range queries in sensor networks. In: ACM Conference on Embedded Networked Sensor Systems (SenSys 03), pp. 63–75 (2003)Google Scholar
- 14.Aly, M., Pruhs, K., Chrysanthis, P.K.: KDDCS: a load-balanced in-network data-centric storage scheme for sensor networks. In: ACM Conference on Information and Knowledge Management(CIKM 06), pp. 317–326 (2006)Google Scholar
- 15.Shin, J., You, J., Song, S.: GDCS: energy efficient grid based data centric storage for sensor networks. J Korea Contents Assoc. 9(1), 98–105 (2009)CrossRefGoogle Scholar
- 16.Heinzelman, W.: Application-specific protocol architectures for wireless networks. Ph.D. dissertation, Massachusetts Institute of Technology (2000)Google Scholar
- 17.Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: Energy-eficient communication protocol for wireless microsensor networks. In: International Conference on System Sciences, pp. 30053014 (2000)Google Scholar
- 18.Tang, X. Xu, J.: Extending network lifetime for precision-constrained data aggregation in wireless sensor networks. In: Annual IEEE International Conference on Computer Communications(INFOCOM 06), pp. 1–12 (2006)Google Scholar
- 19.Western Regional Climate Center, http://www.wrcc.dri.edu (2012). Accessed 1 Oct 2012
- 20.Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: TAG: a tiny aggregation service for ad hoc sensor networks. In: Symposium on Operating Systems Design and Implementation, pp. 131–146 (2002)Google Scholar