Enhanced adaptive partitioning in a distributed graph database
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F29142890%3A_____%2F21%3A00048758" target="_blank" >RIV/29142890:_____/21:00048758 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/00216208:11320/21:10429786
Výsledek na webu
<a href="https://www.tandfonline.com/doi/full/10.1080/24751839.2020.1829387" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/24751839.2020.1829387</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/24751839.2020.1829387" target="_blank" >10.1080/24751839.2020.1829387</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Enhanced adaptive partitioning in a distributed graph database
Popis výsledku v původním jazyce
Nowadays, open-source graph databases do not include an inherent mechanism for data relocation that would be based on their usage. They often do not offer even appropriate monitoring that could help to make such a decision. Information about data utilization could, however, work as an input to some decision-making process about more suitable data regrouping that could be much more efficient in terms of intra-network communication. Therefore, we created a module for the graph computational framework TinkerPop that logs traffic generated by the user queries. These logged records serve as an input for the algorithm of Adaptive Partitioning that we enhanced with better balancing, avoidance of local optima and the notion of weighted graphs. This approach yields a 70-80% improvement in intra-network communication, which is comparable to other methods, namely Ja-be-Ja, that offers similar results but has higher computational demands.
Název v anglickém jazyce
Enhanced adaptive partitioning in a distributed graph database
Popis výsledku anglicky
Nowadays, open-source graph databases do not include an inherent mechanism for data relocation that would be based on their usage. They often do not offer even appropriate monitoring that could help to make such a decision. Information about data utilization could, however, work as an input to some decision-making process about more suitable data regrouping that could be much more efficient in terms of intra-network communication. Therefore, we created a module for the graph computational framework TinkerPop that logs traffic generated by the user queries. These logged records serve as an input for the algorithm of Adaptive Partitioning that we enhanced with better balancing, avoidance of local optima and the notion of weighted graphs. This approach yields a 70-80% improvement in intra-network communication, which is comparable to other methods, namely Ja-be-Ja, that offers similar results but has higher computational demands.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
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OECD FORD obor
10200 - Computer and information sciences
Návaznosti výsledku
Projekt
—
Návaznosti
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal Of Information And Telecommunication
ISSN
2475-1839
e-ISSN
—
Svazek periodika
5
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
16
Strana od-do
105-120
Kód UT WoS článku
000710559700001
EID výsledku v databázi Scopus
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