The traditional databases are not capable of handling unstructured data and high volumes
of real-time datasets. Diverse datasets are unstructured lead to big data, and it is laborious …

Today's systems are overwhelmingly designed to move data to computation. This design
choice goes directly against at least three key trends in systems that cause performance …

Background The academic publishing world is changing significantly, with ever-growing
numbers of publications each year and shifting publishing patterns. However, the metrics …

Driven by the tremendous application demands, the Internet of Things (IoT) systems are
expected to fulfill computation-intensive and latency-sensitive sensing and computational …

Data analytics using machine learning (ML) has become ubiquitous in science, business
intelligence, journalism and many other domains. While a lot of work focuses on reducing …

With the booming development of artificial intelligence (AI), a series of relevant applications
are emerging and promoting an all-rounded reform of the industry. As the major technology …

The wide deployment of 4G/5G has enabled connected vehicles as a perfect edge
computing platform for a plethora of new services which are impossible before, such as …

Graph processing has become an important part of various areas, such as machine
learning, computational sciences, medical applications, social network analysis, and many …

Graph analytics power a range of applications in areas as diverse as finance, networking
and business logistics. A common property of graphs used in the domain of graph analytics …

Graph processing has become an important part of various areas of computing, including
machine learning, medical applications, social network analysis, computational sciences …