Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Carmelo Polito"'
Advances in the communication technologies, along with the birth of new communication paradigms leveraging on the power of the social, has fostered the production of huge amounts of data. Old-fashioned computing paradigms are unfit to handle the dime
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4307df88a7fda5b2179cd3498d0a61f8
https://doi.org/10.4018/978-1-7998-5339-8.ch031
https://doi.org/10.4018/978-1-7998-5339-8.ch031
Publikováno v:
International Journal of Information Technologies and Systems Approach. 11:16-47
Advances in the communication technologies, along with the birth of new communication paradigms leveraging on the power of the social, has fostered the production of huge amounts of data. Old-fashioned computing paradigms are unfit to handle the dime
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd15df238ca8315740fc0b8a122128bb
https://doi.org/10.4018/ijitsa.2018010102
https://doi.org/10.4018/ijitsa.2018010102
Publikováno v:
IoTBDS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::442f73da77658f20e751b99e1e35659c
http://hdl.handle.net/11585/729517
http://hdl.handle.net/11585/729517
Publikováno v:
WiMob
Air pollution is an important issue due to its direct impact on human health. To cope with this problem, in urban areas a “monitor and react” approach, based on measurements provided use of static monitoring stations, is commonly adopted introduc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e60d67cf75515e55b9e3d9c1777fccc
http://hdl.handle.net/20.500.11769/323278
http://hdl.handle.net/20.500.11769/323278
Publikováno v:
ISCC
Effective big data analysis is one of the most notable research challenge of the latest few years. Hadoop, the most popular implementation of the MapReduce framework, has today become widespread used for processing large data sets using cloud resourc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efda0282da0abc10dfab0c1c0e28eed7
http://hdl.handle.net/20.500.11769/299930
http://hdl.handle.net/20.500.11769/299930
Publikováno v:
Innovate-Data
The last few years have seen a growing demand of distributed Cloud infrastructures able to process big data generated by geographically scattered sources. A key challenge of this environment is how to manage big data across multiple heterogeneous dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab400d43808619c1847fea5197bbeb3c
http://hdl.handle.net/11585/736225
http://hdl.handle.net/11585/736225
Publikováno v:
Communications in Computer and Information Science ISBN: 9783319333120
ESOCC Workshops
ESOCC Workshops
Internet-of-Things scenarios will be typically characterized by huge amounts of data made available. A challenging task is to effi- ciently manage such data, by analyzing, elaborating and extracting use- ful information from them. Distributed computi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4455e475d1a696c084e927448c116b8c
http://hdl.handle.net/11585/730314
http://hdl.handle.net/11585/730314
Publikováno v:
BDCAT
Big data analysis requires adequate infrastructure and programming paradigms capable of processing large amount of data. Hadoop, the most known open-source implementation of the MapReduce paradigm, is widely employed in big data analysis frameworks.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04e93a027ce0823d2379f125f4ab380b
http://hdl.handle.net/20.500.11769/70686
http://hdl.handle.net/20.500.11769/70686
Publikováno v:
ISCC
In the past two decades there has been a growing interest over the definition of new distributed computational paradigms capable to serve the need of manipulating and analyzing huge amounts of data. Among the others, the MapReduce outstands for popul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8daae50d213b25e9c150feae84fd9487
http://hdl.handle.net/20.500.11769/98803
http://hdl.handle.net/20.500.11769/98803
Publikováno v:
CLOSER (1)
In many application fields such as social networks, e-commerce and content delivery networks there is a constant production of big amounts of data in geographically distributed sites that need to be timely elaborated. Distributed computing frameworks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bba04fd57074d2d3067d22492ddbcd70
http://hdl.handle.net/11585/730108
http://hdl.handle.net/11585/730108