Infrastructure tradeoffs for sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
An analysis of a large scale habitat monitoring application
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Decentralized compression and predistribution via randomized gossiping
Proceedings of the 5th international conference on Information processing in sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
Network correlated data gathering with explicit communication: NP-completeness and algorithms
IEEE/ACM Transactions on Networking (TON)
ACM Transactions on Sensor Networks (TOSN)
Efficient gathering of correlated data in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Correlated data gathering in wireless sensor networks based on distributed source coding
International Journal of Sensor Networks
International Journal of Distributed Sensor Networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
IEEE Transactions on Signal Processing
The capacity of wireless networks
IEEE Transactions on Information Theory
Stable recovery of sparse overcomplete representations in the presence of noise
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
IEEE Transactions on Information Theory
Variance-component based sparse signal reconstruction and model selection
IEEE Transactions on Signal Processing
Efficient measurement generation and pervasive sparsity for compressive data gathering
IEEE Transactions on Wireless Communications
Practical data compression in wireless sensor networks: A survey
Journal of Network and Computer Applications
CloudSense: continuous fine-grain cloud monitoring with compressive sensing
HotCloud'11 Proceedings of the 3rd USENIX conference on Hot topics in cloud computing
In-situ soil moisture sensing: measurement scheduling and estimation using compressive sensing
Proceedings of the 11th international conference on Information Processing in Sensor Networks
Mechanism design for robust resource management to false report in cloud computing systems
Proceedings of the 2nd ACM international conference on High confidence networked systems
Cell-based snapshot and continuous data collection in wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Continuous data aggregation and capacity in probabilistic wireless sensor networks
Journal of Parallel and Distributed Computing
Efficient feedback scheme based on compressed sensing in MIMO wireless networks
Computers and Electrical Engineering
An efficient compressive data gathering routing scheme for large-scale wireless sensor networks
Computers and Electrical Engineering
IEEE/ACM Transactions on Networking (TON)
Compression in wireless sensor networks: A survey and comparative evaluation
ACM Transactions on Sensor Networks (TOSN)
Compressed data aggregation: energy-efficient and high-fidelity data collection
IEEE/ACM Transactions on Networking (TON)
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This paper presents the first complete design to apply compressive sampling theory to sensor data gathering for large-scale wireless sensor networks. The successful scheme developed in this research is expected to offer fresh frame of mind for research in both compressive sampling applications and large-scale wireless sensor networks. We consider the scenario in which a large number of sensor nodes are densely deployed and sensor readings are spatially correlated. The proposed compressive data gathering is able to reduce global scale communication cost without introducing intensive computation or complicated transmission control. The load balancing characteristic is capable of extending the lifetime of the entire sensor network as well as individual sensors. Furthermore, the proposed scheme can cope with abnormal sensor readings gracefully. We also carry out the analysis of the network capacity of the proposed compressive data gathering and validate the analysis through ns-2 simulations. More importantly, this novel compressive data gathering has been tested on real sensor data and the results show the efficiency and robustness of the proposed scheme.