Data-Intensive Computing Paradigms for Big Data
P. Loncar · Annals of DAAAM for ... & proceedings of the ... International DAAAM Symposium · 2018
The development of ICT has led to enormous growth and data accumulation, and thus created the need for proper storage and processing of large data, known as Big Data.The number of data sources like mobile telephones and applications, social networks, digital television, data of various Internet objects and sensors has increased due to the development of technology and the emergence of the IoT, the evolutionary step in the development of the Internet.Analysis and proper interpretations that take place on the latest distributed platforms are key to data-intensive systems from which feedback can be gained in areas such as industry, finance, healthcare, science and education.Distributed computing paradigms are a fundamental component of research and innovation for e-infrastructures with the intent of providing advanced computing, storage resources and network connectivity necessary for modern and multidisciplinary science and society.The aim of this paper is to provide a systematic overview and address challenges of distributed computing paradigms that marked and brought revolution into computing science and are able to store and process large amounts of data.As an example of a big data source, the world's largest particle detector, CERN's LHC is analyzed.