Approximation schemes for covering and packing problems in image processing and VLSI
Journal of the ACM (JACM)
Set k-cover algorithms for energy efficient monitoring in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Near-optimal sensor placements: maximizing information while minimizing communication cost
Proceedings of the 5th international conference on Information processing in sensor networks
Deploying wireless sensors to achieve both coverage and connectivity
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Algorithms for subset selection in linear regression
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
The Journal of Machine Learning Research
Energy efficient monitoring in sensor networks
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
SFO: A Toolbox for Submodular Function Optimization
The Journal of Machine Learning Research
Using location based social networks for quality-aware participatory data transfer
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
2PDA: two-phase data approximation in wireless sensor network
Proceedings of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
Vehicle occlusion model for traffic monitoring
Proceedings of the Second International Workshop on Computational Transportation Science
A case study of participatory data transfer for urban temperature monitoring
W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
Submodularity and its applications in optimized information gathering
ACM Transactions on Intelligent Systems and Technology (TIST)
Pattern recognition in wireless sensor networks in presence of sensor failures
NNECFSIC'12 Proceedings of the 12th WSEAS international conference on Neural networks, fuzzy systems, evolutionary computing & automation
Learning to Infer the Status of Heavy-Duty Sensors for Energy-Efficient Context-Sensing
ACM Transactions on Intelligent Systems and Technology (TIST)
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We consider the problem of monitoring spatial phenomena, such as road speeds on a highway, using wireless sensors with limited battery life. A central question is to decide where to locate these sensors to best predict the phenomenon at the unsensed locations. However, given the power constraints, we also need to determine when to selectively activate these sensors in order to maximize the performance while satisfying lifetime requirements. Traditionally, these two problems of sensor placement and scheduling have been considered separately from each other; one first decides where to place the sensors, and then when to activate them. In this paper, we present an efficient algorithm, ESPASS, that simultaneously optimizes the placement and the schedule. We prove that ESPASS provides a constant-factor approximation to the optimal solution of this NP-hard optimization problem. A salient feature of our approach is that it obtains “balanced” schedules that perform uniformly well over time, rather than only on average. We then extend the algorithm to allow for a smooth power-accuracy tradeoff. Our algorithm applies to complex settings where the sensing quality of a set of sensors is measured, e.g., in the improvement of prediction accuracy (more formally, to situations where the sensing quality function is submodular). We present extensive empirical studies on several sensing tasks, and our results show that simultaneously placing and scheduling gives drastically improved performance compared to separate placement and scheduling (e.g., a 33% improvement in network lifetime on the traffic prediction task).