Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Distributed Source Coding: Symmetric Rates and Applications to Sensor Networks
DCC '00 Proceedings of the Conference on Data Compression
Robust distributed estimation in sensor networks using the embedded polygons algorithm
Proceedings of the 3rd international symposium on Information processing in sensor networks
Spatio-temporal correlation: theory and applications for wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: In memroy of Olga Casals
Gathering correlated data in sensor networks
Proceedings of the 2004 joint workshop on Foundations of mobile computing
Efficient gathering of correlated data in sensor networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
Utility based sensor selection
Proceedings of the 5th international conference on Information processing in sensor networks
Telos: enabling ultra-low power wireless research
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Introduction to Data Compression, Third Edition (Morgan Kaufmann Series in Multimedia Information and Systems)
Lexicographic Maxmin Fairness for Data Collection in Wireless Sensor Networks
IEEE Transactions on Mobile Computing
IEEE Transactions on Parallel and Distributed Systems
Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks
Proceedings of the 6th ACM conference on Embedded network sensor systems
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Canopy closure estimates with GreenOrbs: sustainable sensing in the forest
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
On-line sensing task optimization for shared sensors
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Near optimal multi-application allocation in shared sensor networks
Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
Adaptive decentralized control of underwater sensor networks for modeling underwater phenomena
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Cool: On Coverage with Solar-Powered Sensors
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Distributed spatial clustering in sensor networks
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
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Wireless Sensor Networks (WSNs) are widely used to monitor the physical environment. In a highly redundant sensor network, sensor readings from nearby sensors often have high similarity. In this work, we are interested in how to decide an appropriate sensing rate for each sensor node, in order to maximize the overall Quality-of-Monitoring (QoM), while ensuring that all readings can be transmitted to the sink. Note that a feasible sensing rate allocation should satisfy both energy constraint on each sensor node and flow conservation through the network. In order to capture the statistical correlations among sensor readings, we first introduce the concept of correlation graph. The correlation graph is further decomposed into several correlation components, and sensor readings from the same correlation component are highly correlated. For each correlation component, we defined a general utility function to estimate the QoM. The utility function of each correlation component is a non-decreasing submodular function of the total sensing rates allocated to that correlation component. Then we formulate the QoM-aware sensing rate allocation problem as a utility maximization problem under limited power supply on each node. To tackle this problem, we adopted an efficient algorithm, called Qute, by jointly considering both the energy constraint on each node and flow conservation through the network. Under some settings, we analytically show that Qute can find the optimal QoM-aware sensing rate allocation which achieves the maximum total utility. We conducted extensive testbed verifications of our schemes, and experimental results validate our theoretical results.