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SQL*Cache is associative in nature, in that it supports content-based reasoning and local execution of SQL queries on the cached data, thereby attempting to reduce query response times and increase server throughput.
And branch-and-bound based methods can reduce query delay significantly.
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We show how to reduce queries about property persistence, a common type of universally-quantified query, to an equivalent form that does not quantify over situations and so is amenable to existing reasoning techniques.
We propose SPROUT, a DHT routing algorithm that, by using social links, significantly increases the number of query results and reduces query delays.
We propose, SPROUT, a DHT routing algorithm that by using social links significantly increases the number of query results and reduces query delays.
A declustering scheme distributes data items among multiple disks, thus enabling parallel data access and reducing query response time.
Simulation results show that these features are effective in reducing query delay, improving data availability, and balancing node power consumption with protocol performance.
A client individually identifies a small group of peers who have the same interests as itself to prefetch their entire file indices of the related interests, minimizing unnecessary outgoing queries and significantly reducing query response time.
For the class of deletion repairs among them, we optimize the algorithm by reducing query evaluation to constraint matching, based on the novel concept of support set, which roughly speaking is a portion of the data from which entailment of an ontology query follows.
If its associated counter is less than MinCover, all counters of atoms covered by the bit are increased, and the bit is added to the resulting reduced query fingerprint; otherwise, the bit is discarded.
Supplementary Sections S1 and S3 describe how HAL offers similar compression to gzip and vastly reduced query times when compared with Multiple Alignment Format (MAF).
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