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Data allocation on multiple I/O devices manifests itself in many computing systems, both centralized and distributed. Data is partitioned on multiple I/O devices and clients issue various types of queries to retrieve relevant information. In this paper, we derive necessary and sufficient conditions for a data allocation method to be optimal for two important types of queries: partial match and bounded disagreement search queries. We formally define these query types and derive the optimality conditions based on coding-theoretic arguments. Although these conditions are fairly strict, we show how to construct good allocation methods for practical realistic situations. Not only are the response times bounded by a small value, but also the identification of the relevant answer set is efficient
client-server systems, disc storage, distributed databases, query processing, storage allocation,data allocation method optimality, bounded disagreement search query, partial match query, multiple I/O devices, data partitioning, coding-theoretic argument, relevant information retrieval,Information retrieval, Software libraries, Delay, Network servers, Distributed computing, Sufficient conditions, Information theory, Codes, Distributed databases, Relational databases,Access methods, file organization, maintenance, organization/structure, information theory, file organization, retrieval models, Cartesian product files, multiple disk systems, coding theory.
"The Optimality of Allocation Methods for Bounded Disagreement Search Queries: The Possible and the Impossible", IEEE Transactions on Knowledge & Data Engineering, vol. 18, no. , pp. 1194-1206, September 2006, doi:10.1109/TKDE.2006.149
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