Next century challenges: mobile networking for “Smart Dust”
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Adaptive filters for continuous queries over distributed data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Convex Optimization
Holistic aggregates in a networked world: distributed tracking of approximate quantiles
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Sketching streams through the net: distributed approximate query tracking
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Communication-efficient distributed monitoring of thresholded counts
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
A geometric approach to monitoring threshold functions over distributed data streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Efficient Constraint Monitoring Using Adaptive Thresholds
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Optimization Techniques for Reactive Network Monitoring
IEEE Transactions on Knowledge and Data Engineering
Reactive monitoring of aggregates in Gaussian random field over wireless sensor networks
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
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Motivated by applications of sensor networks, there has been growing interest in monitoring large scale distributed systems. In these applications, we usually wish to monitor a global system condition defined as a function of local network elements parameters. In this paper, we study Reactive Monitoring in sensor networks, which has the benefit of operating in a decentralized manner. Our primary concern in adopting such a monitoring paradigm is reducing the communication cost which is the dominant factor of energy drain in wireless sensor networks. In this study, we address the reactive aggregate monitoring problem by casting the underlying threshold assignment as an optimization problem. This allow us to propose a distributed algorithm to set local thresholds on each sensor node to be adapted to the statistics of the events measured by spatially scattered sensor nodes. Through simulation, we illustrate that the proposed threshold assignment technique can significantly reduce the communication overhead of the monitoring mechanism in sensor networks.