ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술대회 Information Fusion based Agile Streaming Telemetry for Intelligent Traffic Analytics of Softwarized Network
Cited 0 time in scopus Download 0 time Share share facebook twitter linkedin kakaostory
저자
최태상, 윤상식, Sejun Song
발행일
201709
출처
Asia-Pacific Network Operations and Management Symposium (APNOMS) 2017, pp.399-402
DOI
https://dx.doi.org/10.1109/APNOMS.2017.8094158
협약과제
17HH1100, 자기인증 식별자 기반 자율형 신뢰 네트워킹 기술 개발, 정태수
초록
The recent federation of novel softwareization and virtualization architectures as well as Internet of Things (IoT) technologies complicates management of the network and services. In order to cope with expensive and slow network problem detection, isolation, and root cause analysis based on the SNMP driven pull model management, this paper proposes push based open source streaming network traffic analytics technologies by using P4 (Programming Protocol-Independent Packet Processors) INT (Inband Network Telemetry). Real-Time information fusion algorithms on the intelligent edge that correlates multi-source micro and macro streaming telemetry data are proposed. And its proof-of-concept implementation with performance evaluation.
KSP 제안 키워드
Intelligent traffic, Internet of thing(IoT), Multi-source, Network Telemetry, Network Traffic, Open source, Performance evaluation, Proof of concept, Protocol-independent, Real-time information, Root cause analysis