Big Data Process Advancement
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517343" target="_blank" >RIV/70883521:28140/17:63517343 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1007/978-3-319-57264-2_39" target="_blank" >http://dx.doi.org/10.1007/978-3-319-57264-2_39</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-57264-2_39" target="_blank" >10.1007/978-3-319-57264-2_39</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Big Data Process Advancement
Popis výsledku v původním jazyce
Information in this era is thriving to be maintained on a verity of sources. Data is available in different patterns and forms. Combining and processing all different types of datasets in a heterogeneity database is near to impossible, specifically, if the information is moving and changing on many different sources on a continuous basis. Information is represented in different modules and nowadays processing data from various sources can lead to critical risk assessment results. Big Data is a concept introduced to cover the use of different techniques serving the desired goals by processing the given informa‐ tion. Processing huge amount of data is a big challenge for a single machine to perform, in this paper we will discuss this idea and demonstrate a module of clustered machines to work as a single entity towards achieving the desired tasks while working on parallel cohesively. The idea of a solution to combine different machines of different specification processing and power in a single cluster and then distributing input data of various data fairly to most powerful processing and well-designed data type machine in the cluster. Distribution of input data and storing mechanism will depend on machine specification, data processing, the power of a machine, balance loading and data type. We present our suggestion solving method by using Event-B based approach, the Key features of Event-B are the use of set theory as a modelling notation and we propose using the Rodin modelling tool for Event-B that integrates modelling and proving.
Název v anglickém jazyce
Big Data Process Advancement
Popis výsledku anglicky
Information in this era is thriving to be maintained on a verity of sources. Data is available in different patterns and forms. Combining and processing all different types of datasets in a heterogeneity database is near to impossible, specifically, if the information is moving and changing on many different sources on a continuous basis. Information is represented in different modules and nowadays processing data from various sources can lead to critical risk assessment results. Big Data is a concept introduced to cover the use of different techniques serving the desired goals by processing the given informa‐ tion. Processing huge amount of data is a big challenge for a single machine to perform, in this paper we will discuss this idea and demonstrate a module of clustered machines to work as a single entity towards achieving the desired tasks while working on parallel cohesively. The idea of a solution to combine different machines of different specification processing and power in a single cluster and then distributing input data of various data fairly to most powerful processing and well-designed data type machine in the cluster. Distribution of input data and storing mechanism will depend on machine specification, data processing, the power of a machine, balance loading and data type. We present our suggestion solving method by using Event-B based approach, the Key features of Event-B are the use of set theory as a modelling notation and we propose using the Rodin modelling tool for Event-B that integrates modelling and proving.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
CYBERNETICS AND MATHEMATICS APPLICATIONS IN INTELLIGENT SYSTEMS, CSOC2017, VOL 2 Book Series: Advances in Intelligent Systems and Computing
ISBN
978-3-319-57264-2
ISSN
2194-5357
e-ISSN
neuvedeno
Počet stran výsledku
17
Strana od-do
379-396
Název nakladatele
Springer International Publishing AG
Místo vydání
Cham
Místo konání akce
Zlín
Datum konání akce
26. 4. 2017
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—