Accepted by a High Impact Factor International Journal (Five-year average Impact Factor 5.670)
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Accepted by a High Impact Factor International Journal (Five-year average Impact Factor 5.670)
Awais Khan
(MS/Ph.D Integrated Program, 8th semester)
SciSpace: A Scientific Collaboration Workspace for Geo-Distributed HPC Data Centers, accepted in Journal of Future Generation Computer Systems (5-years Impact Factor, 5.670)
(Lead Author: Awais Khan, Corresponding Author: Prof. Youngjae Kim)
Future Generation Computer Systems (FGCS) aims to lead the way in advances in distributed systems, collaborative environments, big data and high-performance computing on such infrastructures as grids, clouds and the large-scale geo-distributed data centers. FGCS’s has a very high impact factor with an average of 5.670 impact factor over past five years.
Awais Khan (PhD Student, currently doing internship at Oak Ridge National Laboratory, TN, USA), Taeuk Kim (MS Graduate, 2019, currently employed at TmaxSoft), and Hyungi Byun (MS Graduate, 2019, currently employed at TmaxSoft) from Laboratory of Advanced System Software (LASS Lab.) have published a journal paper under the supervision of LASS Lab’s director Professor Youngjae Kim in a highly prestigious journal.
The SCISPACE offers a collaboration-friendly scientific workspace equipped with location-aware data access model. SCISPACE is equipped with multiple data indexing and extraction modes and offers query-like searching on top of file system namespace to expedite big data analytics and scientific workflows among scientists participating in collaboration at geo-distributed large-scale data centers. The proposed solution employs distributed metadata management and introduces the notion of namespace-based sharing scope for publishing data to remote data centers via efficient metadata export utility. Furthermore, it also offers a novel template namespace, which empowers collaborators and scientists to selectively control the data sharing and access.
A paper by Awais Khan, a combined master's–doctoral student, has been accepted by a distinguished international journal with a high impact factor (5-year Impact Factor: 5.670).
'SciSpace: A Scientific Collaboration Workspace for Geo-Distributed HPC Data Centers' accepted by the distinguished international journal Future Generation Computer Systems (5-year Impact Factor 5.670)
(Lead author: Awais Khan; corresponding author: Professor Kim Young-jae)
Future Generation Computer Systems (FGCS) is a distinguished international journal in cloud computing, distributed systems, big data and high-performance computing. Its five-year average impact factor is 5.670.
Awais Khan (combined master's–doctoral student, 8th semester, currently on an internship at Oak Ridge National Laboratory under the U.S. Department of Energy), Kim Tae-wook (master's graduate 2019, now working at TmaxSoft) and Byun Hyun-ki (master's graduate 2019, now working at TmaxSoft) of the Laboratory for Advanced System Software (LASS Lab) published the paper in a distinguished international journal with a high impact factor under the supervision of Professor Kim Young-jae of the LASS Lab.
SCISPACE provides users with a collaboration-friendly scientific workspace equipped with a location-based data access model. It supports multiple data indexing and extraction and offers query-based search on top of the file system namespace, thereby enabling big data analysis and high-speed work processing for scientists across geographically distributed, large-scale data centres. The solution presented in the paper provides distributed metadata management and shared namespace functionality, makes use of an efficient metadata extraction utility, and demonstrates that data transfer to remote data centres is possible. It further provides a distinctive template namespace that allows scientists and collaborators to share data and grant access selectively.
In the era of big data, vast amounts of data are geographically scattered. The absence of a system capable of unifying such data is a major factor impeding collaboration among users. The software solution presented in this research unifies geographically distributed data stores into a POSIX interface-based file system and enables query processing, which is expected to increase collaboration among big data users.