Cloud Computing, Big Data & Emerging Topics

Cloud platforms, edge systems, large-scale data, and machine learning meet in this research-focused collection of proceedings from JCC-BD&ET 2020. Rather than following one continuous argument, the volume gathers selected studies that show how researchers are approaching a broad set of computing problems—from infrastructure and data management to specialized applications.

Research across connected computing fields

The papers are grouped into three main areas: cloud and high-performance computing, Big Data, and machine and deep learning. That structure makes it easier to explore a particular interest while also revealing how these disciplines overlap in practice.

From cloud robotics to edge computing

Contributions in the first section address cloud robotics for Industry 4.0, distributed shared memory focused on edge environments, and a malleable TensorFlow implementation. The section also includes research on rapid viral-disease propagation analysis and architectural criteria for data-intensive machine-learning platforms.

Big Data, knowledge graphs, and real-time systems

The Big Data papers examine harmonizing data with a knowledge graph and optimizing data management in a real-time analysis system for intensive care. These topics offer readers a view into different challenges in organizing and processing data for complex applications.

Machine learning in varied applications

The collection’s machine- and deep-learning section ranges across astronomical identification, crop classification using satellite imagery, raw-audio classification, and automatic generation of affective playlists. Together, these studies show the variety of problems addressed through learning-based methods.

A useful research reference

With 11 peer-reviewed papers selected from 36 submissions, these proceedings are suited to researchers, postgraduate students, and computing practitioners looking for focused examples across cloud computing, Big Data, and machine learning. Browse by topic, or use the collection to discover how distinct research questions are being tackled across contemporary computer science.