RAM^3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware software layer between multimedia stream analysis techniques and Big Data streaming platforms, so as to facilitate the implementation of the former on top of the latter. Indeed, the use of Big Data platforms can give way to the efficient management and analysis of large data amounts, but they require the user to concentrate on issues related to distributed computing since their services are often too raw. The use of RAM 3 S greatly simplifies deploying non-parallel techniques to platforms like Apache Storm or Apache Flink, a fact that is demonstrated by the four different use cases we describe here. We detail the lessons we learned from exploiting RAM 3 S to implement the detailed use cases.
Rammed, or What RAM^3S Taught Us / I. Bartolini, M. Patella. - STAMPA. - (2020), pp. 3429098.11-3429098.15. (Intervento presentato al convegno 22nd International Conference on Information Integration and Web-based Applications & Services (iiWAS2020) tenutosi a Chiang Mai, Thailand nel 30 November - 2 December 2020) [10.1145/3428757.3429098].
Rammed, or What RAM^3S Taught Us
I. Bartolini
;M. Patella
2020
Abstract
RAM^3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware software layer between multimedia stream analysis techniques and Big Data streaming platforms, so as to facilitate the implementation of the former on top of the latter. Indeed, the use of Big Data platforms can give way to the efficient management and analysis of large data amounts, but they require the user to concentrate on issues related to distributed computing since their services are often too raw. The use of RAM 3 S greatly simplifies deploying non-parallel techniques to platforms like Apache Storm or Apache Flink, a fact that is demonstrated by the four different use cases we describe here. We detail the lessons we learned from exploiting RAM 3 S to implement the detailed use cases.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
