Earticle

초록

영어

Ubiquitous computing devices recently are increasing requirements of high-level
performance management automation, and therefore a system management is changing from
a conventional central administration to autonomic computing. Many research centers are
conducting various studies on self-healing method. However, most existing research focuses
on healing after a system error has already occurred. In order to solve this problem, a
prediction model is required to recognize operating environments and predict error
occurrence. In this paper, we present how to predict the performance of system using hybrid
prediction model. This hybrid prediction models adopts a selective healing model according
to system context, for self-diagnosis and prediction of errors when using the four algorithms.
In this paper, we evaluate the prediction time of the hybrid prediction model prototype and
the performance of the target system’s workload. In addition, the prediction is compared with
existing research and the effectiveness is demonstrated by experiment.

목차

Abstract
 1. Introduction
 2. Related works
 3. Prediction Algorithms
 4. Proposed Approach
  4.1 A proposed Architecture for self-healing system
  4.2 Applying TMR method
  4.3 Hybrid Prediction algorithm for Self-healing
 5. Implementation and Evaluation
 6. Conclusions
 7. References

키워드

저자

• Giljong Yoo [ School of Information and Communication Engineering, Sungkyunkwan University, Suwon 400-746, South Korea ]
• Jeongmin Park [ School of Information and Communication Engineering, Sungkyunkwan University, Suwon 400-746, South Korea ]
• Eunseok Lee [ School of Information and Communication Engineering, Sungkyunkwan University, Suwon 400-746, South Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605