On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
Proceedings of the 17th International Conference on Data Engineering
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Maintaining Sliding Window Skylines on Data Streams
IEEE Transactions on Knowledge and 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
Parallel Computation of Skyline Queries
HPCS '07 Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Efficient computation of reverse skyline queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Angle-based space partitioning for efficient parallel skyline computation
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Skyframe: a framework for skyline query processing in peer-to-peer systems
The VLDB Journal — The International Journal 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
Parallelizing skyline queries for scalable distribution
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Parallelizing progressive computation for skyline queries in multi-disk environment
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
A survey of skyline processing in highly distributed environments
The VLDB Journal — The International Journal on Very Large Data Bases
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Skyline queries have attracted considerable attention over the last few years, mainly due to their ability to return interesting objects without the need for user-defined scoring functions. In this work, we study the problem of distributed skyline computation and propose an adaptive algorithm towards controlling the degree of parallelism and the required network traffic. In contrast to state-of-the-art methods, our algorithm handles efficiently diverse preferences imposed on attributes. The key idea is to partition the data using a grid scheme and for each query to build on-the-fly a dependency graph among partitions which can help in effective pruning. Our algorithm operates in two modes: (i) full-parallel mode, where processors are activated simultaneously or (ii) cascading mode, where processors are activated in a cascading manner using propagation of intermediate results, thus reducing network traffic and potentially increasing throughput. Performance evaluation results, based on real-life and synthetic data sets, demonstrate the scalability with respect to the number of processors and database size.