Kriging for Localized Spatial Interpolation in Sensor Networks

Authors:
Muhammad Umer;Lars Kulik;Egemen Tanin
Affiliations:
National ICT Australia, Department of Computer Science & Software Engineering, University of Melbourne, Victoria, Australia 3010;National ICT Australia, Department of Computer Science & Software Engineering, University of Melbourne, Victoria, Australia 3010;National ICT Australia, Department of Computer Science & Software Engineering, University of Melbourne, Victoria, Australia 3010
Venue:
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
Year:
2008

Citing 5
Cited 1

Distributed regression: an efficient framework for modeling sensor network data

Proceedings of the 3rd international symposium on Information processing in sensor networks
The holes problem in wireless sensor networks: a survey

ACM SIGMOBILE Mobile Computing and Communications Review
Constraint chaining: on energy-efficient continuous monitoring in sensor networks

Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Estimation in sensor networks: a graph approach

IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Boundary recognition in sensor networks by topological methods

Proceedings of the 12th annual international conference on Mobile computing and networking

Leveraging redundancy in sampling-interpolation applications for sensor networks: A spectral approach

ACM Transactions on Sensor Networks (TOSN)

Quantified Score

Hi-index	0.00

Visualization

Abstract

The presence of coverage holes can adversely affect the accurate representation of natural phenomena being monitored by a Wireless Sensor Network (WSN). Current WSN research aims at solving the coverage holes problem by deploying new nodes to maximize the coverage. In this work, we take a fundamentally different approach and argue that it is not always possible to maintain exhaustive coverage in large scale WSNs and hence coverage strategies based solely on the deployment of new nodes may fail. We suggest spatial interpolation as an alternative to node deployment and present Distributed Kriging (DISK), a localized method to interpolate a spatial phenomenon inside a coverage hole using available nodal data. We test the accuracy and cost of our scheme with extensive simulations and show that it is significantly more efficient than global interpolations.