SPASS: Scalable and Energy-efficient Data Acquisition in Sensor Databases

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Author

M. H. Ali, Walid G. Aref, and Cristina Nita-Rotaru

Tech report number

CERIAS TR 2005-122

Entry type

proceedings

Abstract

Scalability and energy management issues are crucial for sensor network databases. In this paper, we introduce the Sharing and PArtitioning of Stream Spectrum (SPASS) pro- tocol as a new approach to provide scalability with re- spect to the number of sensors and to manage the power consumption efficiently. The spectrum of a sensor is the range/distribution of values read by that sensor. Close-by sensors tend to give similar readings and, consequently, ex- hibit similar spectra. We propose to combine similar spectra into one global spectrum that is shared by all contributing sensors. Then, the global spectrum is partitioned among the sensors such that each sensor carries out the responsibility of managing a partition of the spectrum. Spectrum sharing and partitioning require continuous coordination to balance the load over the sensors. Experimental results show that the SPASS protocol relieves a sensor database system from the burden of data acquisition in large-scale sensor networks and reduces the per-sensor power consumption.

Date

2005

Booktitle

MobiDE

Key alpha

SPASS: Scalable and Energy-efficient Data Acquisition in Sensor Databases

Publisher

ACM

School

Purdue University

Affiliation

Department of Computer Science

Publication Date

2005-01-01

Copyright

2005 ACM

BibTex-formatted data

To refer to this entry, you may select and copy the text below and paste it into your BibTex document. Note that the text may not contain all macros that BibTex supports.

@Proceedings{ SPASS: Scalable and Energy-efficient Data Acquisition in Sensor Databases,
	title = "SPASS: Scalable and Energy-efficient Data Acquisition in Sensor Databases",
	author = "M. H. Ali,  Walid G. Aref, and  Cristina Nita-Rotaru",
	year = "2005",
	booktitle = "MobiDE",
	publisher = "ACM",
	school = "Purdue University",
	abstract = "Scalability and energy management issues are crucial for 
sensor network databases. In this paper, we introduce the 
Sharing and PArtitioning of Stream Spectrum (SPASS) pro- 
tocol as a new approach to provide scalability with re- 
spect to the number of sensors and to manage the power 
consumption efficiently. The spectrum of a sensor is the 
range/distribution of values read by that sensor. Close-by 
sensors tend to give similar readings and, consequently, ex- 
hibit similar spectra. We propose to combine similar spectra 
into one global spectrum that is shared by all contributing 
sensors. Then, the global spectrum is partitioned among the 
sensors such that each sensor carries out the responsibility 
of managing a partition of the spectrum. Spectrum sharing 
and partitioning require continuous coordination to balance 
the load over the sensors. Experimental results show that 
the SPASS protocol relieves a sensor database system from 
the burden of data acquisition in large-scale sensor networks 
and reduces the per-sensor power consumption.",
	affiliation = "Department of Computer Science",
	copyright = "2005 ACM",
}