Vector based adaptive sampling in wireless sensor networks

Authors:
Aravind Mohanoor;Sridhar Radhakrishnan;Thomas Hughes
Affiliations:
School of Computer Science, University of Oklahoma, Norman, OK;School of Computer Science, University of Oklahoma, Norman, OK;School of Computer Science, University of Oklahoma, Norman, OK
Venue:
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
Year:
2010

Citing 3
Cited 0

Ambient intelligence: industrial research on a visionary concept

Proceedings of the 2003 international symposium on Low power electronics and design
Data Management in the Worldwide Sensor Web

IEEE Pervasive Computing
ASAP: An Adaptive Sampling Approach to Data Collection in Sensor Networks

IEEE Transactions on Parallel and Distributed Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

While in-network aggregation and query processing are the common forms of collecting data in a typical wireless sensor network, continuous monitoring allows for more complex querying of the data collected. The process of collecting this data subject to constraints on the network resources is termed adaptive sampling. In this paper we present a simple quantitative scheme for adaptive sampling by using a vector of suitably defined parameters. The adaptive sampling vector (ASV) specifies the baseline of the data which needs to be collected to meet information quality needs.