Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Maximal vector computation in large data sets
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
Algorithms and analyses for maximal vector computation
The VLDB Journal — The International Journal on Very Large Data Bases
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A clustering based approach for skyline diversity
Expert Systems with Applications: An International Journal
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In this paper, we present our work on evaluating the skyline algorithms BNL, SFS, and a variant of LESS in PostgreSQL. It is well known that the performance of skyline queries is sensitive to a number of parameters. From extensive experiments on skyline implementations we have discovered several rules, which are remarkably simple and useful, but hard to obtain from theoretical investigation. Our findings are beneficial for developing heuristics for the skyline query optimization, and in the meantime, provide some insight for a deeper understanding of the skyline query characteristics.