Individual data might not be thought of as that important for business purposes. However, Big Data analytics use cases are increasing, because individual data can become a valuable data aggregate from which any hidden information can be found, once it’s collected into large volumes. Big Data. Known as one of conventional Big Data analytics technologies, Hadoop is a widely accepted technology to analyze structured/ unstructured Big Data to date. However, Hadoop has a high possibility for response time latency with larger data because of batch processing systems, which makes it difficult to do real time analysis for massive amounts of high speed event data under the current business environment and market conditions. In this paper, open source CEP (Complex Event Processing)-based technologies are used as an alternative for rapidly changing business, thereby developing the real time analytics system that enables us to analyze over thousands of event streams per second on a real time basis without latency, in order to be applicable to medical institution ERP systems.
목차
Abstract 1. Introduction 2. Related Works 2.1. Big Data 2.2. Hadoop 2.3. CEP(Complex Event Processing) 2.4. Hadoop and CEP for Big Data Approach 2.5. Definitions and Characteristics of NoSQL 3. System Compositions and Designs 4. System Implementation 5. Conclusion References
보안공학연구지원센터(IJSEIA) [Science & Engineering Research Support Center, Republic of Korea(IJSEIA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Software Engineering and Its Applications
간기
월간
pISSN
1738-9984
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Software Engineering and Its Applications Vol.9 No.7