Critical data points retrieving method for big sensory data in wireless sensor networks

Eurasip Journal on Wireless Communications and Networking

Volumn 2016, Issue 1, 2016, Pages 1-14

  Zhu, Tongxin ^a   Cheng, Siyao ^a   Cai, Zhipeng ^b   Li, Jianzhong ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b GEORGIA STATE UNIVERSITY   (United States)

Author keywords

Adaptive sampling; Critical points; Wireless sensor networks

Indexed keywords

DATA ACQUISITION; SENSORY ANALYSIS;

ACQUISITION PROCESS; ADAPTIVE SAMPLING; ANALYSIS AND SIMULATION; CRITICAL POINTS; DATA-ACQUISITION ALGORITHM; LAGRANGE INTERPOLATIONS; PROCESSING ABILITY; WIRELESS SENSOR NETWORK (WSNS);

WIRELESS SENSOR NETWORKS;

EID: 84954318380     PISSN: 16871472     EISSN: 16871499     Source Type: Journal    
DOI: 10.1186/s13638-015-0505-0     Document Type: Article

References (34)

1. Darpa Sensit Program. http://comlab.ecs.syr.edu/workshop2002/files/RichardButler.pdf.
2. S Kumar, D Shepherd, in Proc. 4th Int. Conf. on Information Fusion. SensIT: Sensor information technology for the warfighter (Elsevier, 2001), pp. 1–7.
3. Z Cai, Z-Z Chen, G Lin, A 3.4713-approximation algorithm for the capacitated multicast tree routing problem. Theor. Comput. Sci.410(52), 5415–5424 (2008).
4. Z Cai, G Lin, G Xue, in Proceedings of 11th Annual International Conference on Computing and Combinatorics 2005 (COCOON). Improved approximation algorithms for the capacitated multicast routing problem (SpringerKunming, China, 2005), pp. 136–145.
5. M Li, Y Liu, L Chen, Nonthreshold-based event detection for 3d environment monitoring in sensor networks. IEEE Trans. Knowl. Data Eng.20(12), 1699–1711 (2008).
6. Greenorbs. http://greenorbs.org/.
7. K Liu, M Li, Y Liu, X Li, M Li, H Ma, in Proceedings of the 18th Annual IEEE International Conference on Network Protocols, ICNP 2010, Kyoto, Japan, 5–8 October, 2010. Exploring the hidden connectivity in urban vehicular networks (IEEE Computer Society, 2010), pp. 243–252.
8. B Barbagli, L Bencini, I Magrini, G Manes, A Manes, in Proceedings of the 7th International Wireless Communications and Mobile Computing Conference, IWCMC 2011, Istanbul, Turkey, 4–8 July, 2011. A real-time traffic monitoring based on wireless sensor network technologies (IEEE, 2011), pp. 820–825.
9. Structural Health Monitoring of the Golden Gate Bridge. http://www.cs.berkeley.edu/?binetude/ggb/.
10. S Kim, S Pakzad, DE Culler, J Demmel, G Fenves, S Glaser, M Turon, in Proceedings of the 6th International Conference on Information Processing in Sensor Networks, IPSN 2007, Cambridge, Massachusetts, USA, April 25–27, 2007. Health monitoring of civil infrastructures using wireless sensor networks (ACM, 2007), pp. 254–263.
11. S Kim, S Pakzad, DE Culler, J Demmel, G Fenves, S Glaser, M Turon, in Proceedings of the 4th International Conference on Embedded Networked Sensor Systems, SenSys 2006, Boulder, Colorado, USA, October 31 - November 3, 2006. Wireless sensor networks for structural health monitoring (Springer, 2006), pp. 427–428.
12. JT Overpeck, GA Meehl, S Bony, DR Easterling, Climate data challenges in the 21 st century. Science (Washington). 331(6018), 700–702 (2011).
13. S Cheng, Z Cai, J Li, Curve query processing in wireless sensor networks. IEEE Trans. Veh. Technol.64(11), 5198–5209 (2015).
14. J Li, S Cheng, (ε, δ)-approximate aggregation algorithms in dynamic sensor networks. IEEE Trans. Parallel Distrib. Syst.23(3), 385–396 (2012).
15. S Cheng, J Li, in 29th IEEE International Conference on Distributed Computing Systems (ICDCS 2009), 22–26 June 2009, Montreal, Québec, Canada. Sampling based (ε, δ)-approximate aggregation algorithm in sensor networks (IEEE Computer Society, 2009), pp. 273–280.
16. S Cheng, J Li, Q Ren, L Yu, in INFOCOM 2010. 29th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 15–19 March 2010, San Diego, CA, USA. Bernoulli sampling based (ε, δ)-approximate aggregation in large-scale sensor networks (IEEE, 2010), pp. 1181–1189.
17. Z He, Z Cai, S Cheng, X Wang, Approximate aggregation for tracking quantiles in wireless sensor networks. Theor. Comput. Sci. 607:, 381–390 (2015).
18. S Cheng, J Li, L Yu, in Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25–30, 2012. Location aware peak value queries in sensor networks (IEEE, 2012), pp. 486–494.
19. A Silberstein, R Braynard, CS Ellis, K Munagala, J Yang, in Proceedings of the 22nd International Conference on Data Engineering, ICDE 2006, 3–8 April 2006, Atlanta, GA, USA. A sampling-based approach to optimizing top-k queries in sensor networks (IEEE Computer Society, 2006), p. 68.
20. M Wu, J Xu, X Tang, W Lee, Top-k monitoring in wireless sensor networks. IEEE Trans. Knowl. Data Eng.19(7), 962–976 (2007).
21. I Su, Y Chung, C Lee, Y Lin, Efficient skyline query processing in wireless sensor networks. J. Parallel Distrib. Comput.70(6), 680–698 (2010).
22. Z Wu, M Wang, L Yuan, H Jiang, in Proceedings of the 2nd International Conference on BioMedical Engineering and Informatics (BMEI). Optimized routing structure based skyline query algorithm in wireless sensor network (IEEE Computer SocietyTianjin, China, 2009), pp. 1–5.
23. J Cao, LE Li, A Chen, T Bu, in Proceedings of the 1st ACM Workshop on Mobile Internet Through Cellular Networks. Incremental tracking of multiple quantiles for network monitoring in cellular networks (ACMNew York, NY, USA, 2009), pp. 7–12.
24. Z Huang, L Wang, K Yi, Y Liu, in Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2011, Athens, Greece, June 12–16, 2011. Sampling based algorithms for quantile computation in sensor networks (ACM, 2011), pp. 745–756.
25. J Li, S Cheng, H Gao, Z Cai, Approximate physical world reconstruction algorithms in sensor networks. IEEE Trans. Parallel Distrib. Syst.25(12), 3099–3110 (2014).
26. S Cheng, J Li, Z Cai, in Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14–19, 2013. O(ε)-approximation to physical world by sensor networks, (2013), pp. 3084–3092.
27. C-E Froberg, CE Frhoberg, Introduction to Numerical Analysis (Addison-Wesley Reading, Massachusetts, USA, 1969).
28. MJD Powell, Approximation Theory and Methods (Cambridge university press, England, 1981).
29. T Lindgren, J Sanchez, J Hall, in Graphics Gems III. Curve tessellation criteria through sampling (ACMSan Diego, CA, USA, 1992), pp. 262–265.
30. M Rahimi, R Safabakhsh, in Proceedings of the IEEE International Conference on Wireless Communications, Networking and Information Security, WCNIS 2010, 25–27 June 2010, Beijing, China. Adaptation of sampling in target tracking sensor networks (IEEE, 2010), pp. 301–305.
31. C Alippi, G Anastasi, MD Francesco, M Roveri, An adaptive sampling algorithm for effective energy management in wireless sensor networks with energy-hungry sensors. IEEE Trans. Instrum. Meas.59(2), 335–344 (2010).
32. A Jain, EY Chang, in Proceedings of the 1st Workshop on Data Management for Sensor Networks, in Conjunction with VLDB, DMSN 2004, Toronto, Canada, August 30, 2004. Adaptive sampling for sensor networks (ACM, 2004), pp. 10–16.
33. YW Law, S Chatterjea, J Jin, T Hanselmann, M Palaniswami, in Proceedings of the International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly, IWCMC 2009, Leipzig, Germany, June 21–24, 2009. Energy-efficient data acquisition by adaptive sampling for wireless sensor networks (ACM, 2009), pp. 1146–1151.
34. P Padhy, RK Dash, K Martinez, NR Jennings, in 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, May 8–12, 2006. A utility-based sensing and communication model for a glacial sensor network (ACM, 2006), pp. 1353–1360.