Distributed Query Optimization and Indexing Schemas in Cloud Server
Using Canonicalization Approach
(Sprache: Englisch)
Optimal Query Anatomization uses the similarity and filtering approaches for storing, processing and managing huge amounts of data.To increase the metadata extraction accuracy an optimal distributed query processing based on canonicalization algorithm is...
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Optimal Query Anatomization uses the similarity and filtering approaches for storing, processing and managing huge amounts of data.To increase the metadata extraction accuracy an optimal distributed query processing based on canonicalization algorithm is proposed. It is then filtered using a cuckoo filter for obtaining the possible relevant queries. Then, the qualified sequence templates are stored in the template database. Now, the canonical strings of the user query are checked with the template database for sequence matching. Finally, query mapping is done for the matched sequence.
Autoren-Porträt von K. Senthil, P. Chitra
Senthil, K.Senthil K, Research Scholar at TCE, Madurai,India, B.E(EEE),Madurai Kamaraj University,Madurai,India(2004), M.Tech(CSE),S.R.M University, Chennai,India(2006).Dr.P.Chitra, Professor at TCE,Madurai,India. PhD in CSE, Anna University,Chennai,India(2011). Area of interest: Distributed Computing, Parallel Processing & Networks.
Bibliographische Angaben
- Autoren: K. Senthil , P. Chitra
- 2019, 132 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6139461294
- ISBN-13: 9786139461295
Sprache:
Englisch
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