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2019, vol. 47, br. 4, str. 711-722
Usklađivanje složenosti klastera u mrežnim sistemima
Russian Academy Sciences, V.A. Trapeznikov Institute of Control Sciences, Moscow, Russia

e-adresabbc@ipu.ru
Ključne reči: big data; data mining; alignment; cluster; network partitioning; NP-hardness; heuristics
Sažetak
Ovaj rad razmatra strukture za upravljanje podacima i klaster tehnologije u mrežama velikih skala. Suboptimalni problemi particije mreže formulisani su na osnovu usklađivanja indeksa složenosti. Predložen je metod za rešavanje ovih problema, posebno određivanje broja klastera podataka i njihovih granica. Opisana je višestepena iteraktivna šema za semantičko pretraživanje podataka iz velikih dokumenata sa međuzavisnim sekcijama. U prvoj fazi, procenjuje se "a-priori" kompleksnost pretraživanja podataka iz ovih sekcija. Onda, rafiniše se ova složenost uzimajući u obzir otkrivenih podataka iz pretraživanja podataka iz susednih sekcija. Na osnovu toga, formira se konačna particija skupa podataka velikog dokumenta na klastere, u okolnostima rokova i ograničenja finansijskih sredstava. Predložene metode primenjene su u nekim transportnim projektima velikih skala.
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O članku

jezik rada: engleski
vrsta rada: neklasifikovan
DOI: 10.5937/fmet1904711E
objavljen u SCIndeksu: 10.10.2019.
Creative Commons License 4.0

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