Due to the explosive growth of internet of things, social media,and mobile systems, massive data including structured, semi-structured, and unstructured data are generated. How to efficiently store, manage and transfer the data is becoming one of challenging questions. Big data system is supposed to solve or alleviate this challenge.

Designing a big data system with high performance, incremental scalability and fault tolerance is very important. It also poses great challenges and opportunities for data management and analytics. Additionally, the system scale employed to manage big data grows with the increase of the data volume. Therefore, many other features like power efficiency and total ownership costs are very important for big data systems as well. Furthermore, for a specific application scenario such as graph processing, designing a big data system with emerging hardware such as flash memory and GPU will offer useful insights into new methods of the application domain and even further.

The purpose of this special session on Big Data Systems is to provide a forum for researchers and scientists from diverse backgrounds to exchange and discuss their state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of advanced technologies in big data systems.

This is a special session of the 13th IEEE International Conference on Cyber, Physical and Social Computing (http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php). Please submit your paper via the submission site (TBA) and select the special session of “Advanced Technologies in Big Data Systems” marked with “CPSComBDS”.

Accepted conference papers will be published by IEEE (IEEE-DL and EI indexed). Selected papers, after further extensions and revisions, will be recommended to journal special issues. More details at the conference website:
http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php

Potential topics include but are not limited to:

•    Design and implementation of big data systems
•    Big data platform
•    Data center architecture
•    Data storage and management
•    Fault tolerance of big data systems
•    Data deduplication
•    Big Data Analytics
•    Innovative methods for big data analytics
•    Performance of big data systems
•    Benchmarking big data systems
•    Security and privacy of big data system
•    QoS of big data system
•    Reliability of big data system
•    Power efficiency of big data system
•    Cluster computing
•    Parallel and distributed computing
•    High performance computing
•    Green computing

Session Chairs：
Yuhui Deng, Jinan University, China
Yi Zhou, Columbus State University, USA