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 …

Big Data has emerged in the past few years as a new paradigm providing abundant data
and opportunities to improve and/or enable research and decision-support applications with …

The next generation of AI applications will continuously interact with the environment and
learn from these interactions. These applications impose new and demanding systems …

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 …

MapReduce is emerging as a generic parallel programming paradigm for large clusters of
machines. This trend combined with the growing need to run machine learning (ML) …

This paper introduces CIEL, a universal execution engine for distributed data-flow programs.
Like previous execution engines, CIEL masks the complexity of distributed programming …

Hyracks is a new partitioned-parallel software platform designed to run data-intensive
computations on large shared-nothing clusters of computers. Hyracks allows users to …

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 …

Distributed programming has become a topic of widespread interest, and many
programmers now wrestle with tradeoffs between data consistency, availability and latency …

Managing data and computation is at the heart of datacenter computing. Manual
management of data can lead to data loss, wasteful consumption of storage, and laborious …