원문정보
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
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