Computing all skyline probabilities for uncertain data
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Identifying interesting instances for probabilistic skylines
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Asymptotically efficient algorithms for skyline probabilities of uncertain data
ACM Transactions on Database Systems (TODS)
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The skyline of a data set is the set of points that are not dominated by any other point. A number of algorithms have been developed for skyline computation on centralized databases, but only a little work has been done on skyline retrieval on P2P networks. Existing P2P skyline algorithms are particularly designed for subspace skylining, or con- strained to certain network infrastructure, thus inapplica- ble for others. This paper proposes a novel skyline retrieval algorithm based on one of the most distinguished P2P net- work infrastructures, Chord, and minimizes the bandwidth consumption as well as the number of visited nodes. The algorithm progressively outputs the skyline points and pro- vides means to keep query load balance. Both theoretical analysis and experimental results confirm the efficiency and scalability of the proposed algorithm.