Earticle

초록

영어

Big data management is becoming an increasingly important issue in both industry and academia of information science community today. One of the important categories of big data generated from software systems is log data. Log data is generally used for better services in various service providers and can also be used to improve system reliability. In this paper, we propose a novel big data management architecture specialized for log data. The proposed architecture provides a scalable log management system that consists of client and server side modules for efficient handling of log data. To support large and simultaneous log data from multiple clients, we adopt the Hadoop infrastructure in the server-side file system for storing and managing log data efficiently. We implement the proposed architecture to support various client environments and validate the efficiency through measurement studies. The results show that the proposed architecture performs better than the existing logging architecture by 42.8% on average. All components of the proposed architecture are implemented based on open source software and the developed prototypes are now publicly available.

목차

Abstract
 1. Introduction
 2. Basic Architecture of LogStore
 3. Store Log Data with Hadoop Infrastructures
 4. Implementations
  4.1 File Tailing Architecture
  4.2 Log Appender Architecture
  4.3 AMQPAppender for log4j
 5. Performance Evaluations
 6. Conclusions 
 Acknowledgment
 References

키워드

저자

• Julie Kim [ Dept. of Computer Science and Engineering, Ewha University, Seoul, 120-750, Korea ]
• Hyokyung Bahn [ Dept. of Computer Science and Engineering, Ewha University, Seoul, 120-750, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380