GPSR: greedy perimeter stateless routing for wireless 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
GHT: a geographic hash table for data-centric storage
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Resilient Data-Centric Storage in Wireless Ad-Hoc Sensor Networks
MDM '03 Proceedings of the 4th International Conference on Mobile Data Management
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Data-centric storage in sensornets with GHT, a geographic hash table
Mobile Networks and Applications
Data Dissemination with Ring-Based Index for Wireless Sensor Networks
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
Multi-dimensional range queries in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Coping with irregular spatio-temporal sampling in sensor networks
ACM SIGCOMM Computer Communication Review
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
A framework for time indexing in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Maximal vector computation in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Efficient computation of the skyline cube
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Robust Cardinality and Cost Estimation for Skyline Operator
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Skyline Queries Against Mobile Lightweight Devices in MANETs
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Progressive skylining over web-accessible databases
Data & Knowledge Engineering
Efficient progressive processing of skyline queries in peer-to-peer systems
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Preprocessing in a tiered sensor network for habitat monitoring
EURASIP Journal on Applied Signal Processing
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Approaching the skyline in Z order
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Parallel Distributed Processing of Constrained Skyline Queries by Filtering
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Towards energy-efficient skyline monitoring in wireless sensor networks
EWSN'07 Proceedings of the 4th European conference on Wireless sensor networks
Continuously maintaining sliding window skylines in a sensor network
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Energy-efficient filtering for skyline queries in cluster-based sensor networks
Computers and Electrical Engineering
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How to process a skyline query efficiently has received considerable attention in recent years. A skyline query identifies a set of non-dominated data records in a multidimensional dataset. Whereas most previous studies have resolved this problem in a centralized environment, this work considers it in a distributed sensor network environment. An algorithm, known as Skyline Sensor Algorithm (SkySensor), is presented to efficiently retrieve skyline results from a sensor network. A cluster-based architecture is designed in SkySensor to collect all sensor readings. A pruning method is then proposed to progressively sift out the skyline results from the sensor network. SkySensor avoids the need of collecting data from all sensors in the network, which is an extremely expensive action, when searching for the skyline results. The performance study indicates that SkySensor is highly efficient, and significantly outperforms previous methods in processing skyline queries.