Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Habitat monitoring: application driver for wireless communications technology
SIGCOMM LA '01 Workshop on Data communication in Latin America and the Caribbean
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Medians and beyond: new aggregation techniques for sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Power-conserving computation of order-statistics over sensor networks
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the 3rd international conference on Embedded networked sensor systems
Sweeps over wireless sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
A distributed algorithm for managing multi-target identities in wireless ad-hoc sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Decentralized sensor fusion with distributed particle filters
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Distributed Tracking in Multihop Sensor Networks With Communication Delays
IEEE Transactions on Signal Processing
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In this paper, we consider a problem of recognizing the shape of an event region in wireless sensor networks (WSNs). The basic idea of our algorithm is to focus on a distance field defined by the hop count from the boundary of the event region. By constructing such field, we can easily identify several critical points in the event region (e.g., local maximum and saddle point), which will be used to characterize the shape of the event region. The communication cost required for a shape recognition significantly decreases compared with a naive centralized scheme by selectively allowing those critical points to send a notification message to a data aggregation point. The performance of the proposed scheme is evaluated by simulation. The result of simulations indicates that: 1) accuracy of shape recognition depends on the density of the underlying WSN, while it is robust against the lack of sensors in a particular region in the field, and 2) the cost of shape recognition significantly decreases by applying the proposed scheme.