KREONET

N-S-C- Orchestration System and Edge Computing Technology Development

Objective

Developing the N-S-C Integrated Resource Control System for the KREONET, which provides a high-performance network environment through the design and implementation of an orchestrator that integrates networking, storage, and computing resources.

Developing an environment where researchers and users in the science and technology community (including government-funded research institutes and universities) can store, exchange, distribute, and process large-scale scientific data—such as that generated by supercomputers, particle accelerators, and radio telescopes—using edge computing.

Period

January 2022 – December 2023

Funding

KISTI Basic Research Program: Establishment, Operation, and Service of Science and Technology Research Network Infrastructure Based on Future Demands

Description

Kubernetes/container-based storage and computing resource management technology
Networking resource management through SDN-based Virtual Dedicated Network (VDN) integration
Integration with Globus Online for high-speed scientific data transfer and management
Distributed storage integration and edge storage resource allocation and synchronization
Integration and interconnection of heterogeneous storage systems (e.g., Ceph, MinIO, Lustre)
Monitoring and web interface technology based on an integrated resource management system

Expected Benefits

Addresses the shortage of data storage capacity for large-scale scientific data collected from major experimental facilities in the science and technology community.
Ensures high-speed network transmission performance required for data-intensive research by integrating and utilizing virtual dedicated network (VDN) technologies.
Develops a wide range of software tools and functions that allow researchers to store and share data at the edge layer, enabling edge computing–based workflows.
Implements automated and intelligent user interfaces that allow users to efficiently access, manage, and utilize integrated resources across network, computing, and storage layers.
Enhances research productivity through the advancement of a converged infrastructure for data transfer and sharing between domestic and international research institutions.
Provides a stable, high-speed, and distributed storage system and high-bandwidth virtual dedicated networks, enabling high-performance scientific data transfer and sharing between researchers and institutions.
Overcomes limitations faced by big data researchers by offering efficient integration and sharing of computing, storage, and network resources.
Creates synergy for collaborative research through the implementation of an edge computing–based integrated resource management system and a distributed storage environment optimized for cross-disciplinary research.