A bayesian multilevel modeling approach for data query in wireless sensor networks

Honggang Wang, Hua Fang, Kimberly Andrews Espy, Dongming Peng, Hamid Sharif

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In power-limited Wireless Sensor Network (WSN), it is important to reduce the communication load in order to achieve energy savings. This paper applies a novel statistic method to estimate the parameters based on the realtime data measured by local sensors. Instead of transmitting large real-time data, we proposed to transmit the small amount of dynamic parameters by exploiting both temporal and spatial correlation within and between sensor clusters. The temporal correlation is built on the level-1 Bayesian model at each sensor to predict local readings. Each local sensor transmits their local parameters learned from historical measurement data to their cluster heads which account for the spatial correlation and summarize the regional parameters based on level-2 Bayesian model. Finally, the cluster heads transmit the regional parameters to the sink node. By utilizing this statistical method, the sink node can predict the sensor measurements within a specified period without directly communicating with local sensors. We show that this approach can dramatically reduce the amount of communication load in data query applications and achieve significant energy savings.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages859-866
Number of pages8
Volume4489 LNCS
EditionPART 3
StatePublished - 2007
Externally publishedYes
Event7th International Conference on Computational Science, ICCS 2007 - Beijing, China
Duration: May 27 2007May 30 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume4489 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Conference on Computational Science, ICCS 2007
CountryChina
CityBeijing
Period5/27/075/30/07

Fingerprint

Multilevel Modeling
Bayesian Modeling
Wireless Sensor Networks
Wireless sensor networks
Query
Sensor
Sensors
Head
Temporal Correlation
Spatial Correlation
Bayesian Model
Energy Saving
Reading
Energy conservation
Real-time Data
Predict
Communication
Large Data
Vertex of a graph
Statistical method

Keywords

  • Bayesian multilevel modeling
  • Wireless sensor network

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Wang, H., Fang, H., Espy, K. A., Peng, D., & Sharif, H. (2007). A bayesian multilevel modeling approach for data query in wireless sensor networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 3 ed., Vol. 4489 LNCS, pp. 859-866). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4489 LNCS, No. PART 3).

A bayesian multilevel modeling approach for data query in wireless sensor networks. / Wang, Honggang; Fang, Hua; Espy, Kimberly Andrews; Peng, Dongming; Sharif, Hamid.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4489 LNCS PART 3. ed. 2007. p. 859-866 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4489 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, H, Fang, H, Espy, KA, Peng, D & Sharif, H 2007, A bayesian multilevel modeling approach for data query in wireless sensor networks. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 3 edn, vol. 4489 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 4489 LNCS, pp. 859-866, 7th International Conference on Computational Science, ICCS 2007, Beijing, China, 5/27/07.
Wang H, Fang H, Espy KA, Peng D, Sharif H. A bayesian multilevel modeling approach for data query in wireless sensor networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 3 ed. Vol. 4489 LNCS. 2007. p. 859-866. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).
Wang, Honggang ; Fang, Hua ; Espy, Kimberly Andrews ; Peng, Dongming ; Sharif, Hamid. / A bayesian multilevel modeling approach for data query in wireless sensor networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4489 LNCS PART 3. ed. 2007. pp. 859-866 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).
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