Data analytics in massive manufacturing data can extract huge business values while can
also result in research challenges due to the heterogeneous data types, enormous volume …

The primary purpose of this paper is to provide an in-depth analysis of different platforms
available for performing big data analytics. This paper surveys different hardware platforms …

The vertex-centric programming model is an established computational paradigm recently
incorporated into distributed processing frameworks to address challenges in large-scale …

GPS (for Graph Processing System) is a complete open-source system we developed for
scalable, fault-tolerant, and easy-to-program execution of algorithms on extremely large …

The wide proliferation of various wireless communication systems and wireless devices has
led to the arrival of big data era in large-scale wireless networks. Big data of large-scale …

Computational microscopy, as a subfield of computational imaging, combines optical
manipulation and image algorithmic reconstruction to recover multi-dimensional microscopic …

Differential Dataflow Page 1 Differential Dataflow McSherry, Frank D., Murray, Derek G.,
Isaacs, Rebecca, Isard, Michael Chathura Kankanamge 08th November 2016 Page 2 Outline …

Distributed computing frameworks are the fundamental component of distributed computing
systems. They provide an essential way to support the efficient processing of big data on …

In the last two decades, the continuous increase of computational power has produced an
overwhelming flow of data which has called for a paradigm shift in the computing …

Context: In recent years, the valuable knowledge that can be retrieved from petabyte scale
datasets–known as Big Data–led to the development of solutions to process information …