Abstract
Uncertain data arises in many modern applications including sensor networks, data integration, and information extraction. Often this data is distributed and there is a need to do efficient query processing over the data in situ. We focus on answering top-k queries and propose a distributed algorithm TDUD, to efficiently answer top-k queries over distributed uncertain categorical data in queries single round of communication. TDUD uses a distributed index structure composed of local uncertain indexes (LUIs) on local sites and a single global uncertain index (GUI) on a coordinator site. Our algorithm minimizes the amount of communication needed to answer a top-k query by maintaining the mean sum dispersion of the probability distribution on each site. Extensive experiments are conducted to verify the effectiveness and efficiency of the proposed methods in terms of communication costs and response time. We show empirically that TDUD is near-optimal in that it can typically retrieve the top-k query answers by communicating only k tuples in a single round.
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- 1.
We will call this approach NAIV in our experiments.
- 2.
We will call this approach DUTk in our experiments.
- 3.
To avoid having a null value of the SDM (\(M(S,d)\)=0), V should have at least two different values of the attached probabilities. We note that in practice probability values are different.
- 4.
Actually in this case, we can request the top-k tuples approximately.
- 5.
In the example, we are reporting the real number estimates but our algorithm takes the integer floor of this number. See Eq. 2.
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We thank and show our gratitude to Salima Benbernou and Renée Miller for relevant and helpful comments and suggestions that greatly improved the manuscript.
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Benaissa, A., Sahri, S., Ouziri, M. (2020). Top-k Queries over Distributed Uncertain Categorical Data. In: Hameurlain, A., Tjoa, A. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XLIII. Lecture Notes in Computer Science(), vol 12130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62199-8_2
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