In recent years, data storage has emerged as an important research field driven by the demand for scalable structures and technologies to satisfy the growing needs of massive data management and processing. Big Data challenges storage systems with more capacity, scalability and efficient accessibility. Dispersing a huge data object in a large-scale distributed storage system is necessary to enhance data reliability and availability. By introducing redundancy in the system, we can protect data integrity from node failures. As node failures occur frequently in large-scale storage systems, a considerable volume of network traffic is dedicated to the repair of failed storage nodes. Several classes of distributed storage codes, such as regenerating codes, locally repairable codes, have been introduced recently to reduce this overhead and disk input/output cost. However, there still remains substantial research work for advancing distributed storage coding and systems in both theory and applications.
This workshop will provide an excellent platform for researchers and practitioners from academia and industry to exchange ideas and experiences that distributed storage systems can offer to Big Data applications, and to understand the challenges that we need tackle to realize the full potential.
Topics of interest include but are not limited to:
The full manuscript should be at most 8 pages using the 2-column IEEE format. Additional pages will be charged additional fee.
Papers MUST be submitted in PDF format and only through the Online Submission System.
The authors of accepted papers must guarantee that their papers will be presented at the conference. At least one author of each accepted paper must register for the conference in order to include the paper in IEEE Xplore Digital Library.
Authors of accepted papers will be invited to submit a revised and extended version of their paper (at least 30% of additional material) after the workshop to a related special issue of a journal as a special issue in the ZTE Communications.
Our workshop will be held in conjunction with the following workshop: First Workshop on Data-Centric Infrastructure for Big Data Science.
|13:30-15:35||First Workshop on Data-Centric Infrastructure for BigData Science|
|15:50-16:15||RADII: Resource Aware Datacentric CollaboratIon Infrastructure Claris Castillo, Fan Jiang, Charles Schmitt, Ilya Baldin, Arcot Rajasekar (RENCI, UNC-Chapel Hill)|
|16:15-16:40||A Comprehensive Evaluation of NoSQL Datastores in the Context of Historians and Sensor Data Analysis Arun Kumar Kalakanti, Vinay Sudhakaran, Varsha Raveendran, and Nisha Menon (Siemens Technology and Services Pvt. Ltd., Bangalore, India)|
|16:40-17:05||On the Implementation of Zigzag Codes for Distributed Storage System Lijia Lu, Hui Li, Jun Chen, Bing Zhu (Shenzhen Graduate School, Peking University, China), and Weijuan Yin (Shenzhen Huadong Feitian Network Development Co., Ltd., Shenzhen, China)|
|17:05-17:30||Challenges and Opportunities on Network Resource Management in DCN with SDN
Guan Xu, Jun Yang, and Bin Dai (Huazhong University of Science and Technology, China)
Date: 29-October, 2015  Venue: Ballroom H, Hyatt Regency Santa Clara, CA 95054, USA