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- Title
Software aging prediction - a new approach.
- Authors
Parashivamurthy, Shruthi; Cholli, Nagaraj Girish
- Abstract
To meet the users' requirements which are very diverse in recent days, computing infrastructure has become complex. An example of one such infrastructure is a cloud-based system. These systems suffer from resource exhaustion in the long run which leads to performance degradation. This phenomenon is called software aging. There is a need to predict software aging to carry out pre-emptive rejuvenation that enhances service availability. Software rejuvenation is the technique that refreshes the system and brings it back to a healthy state. Hence, software aging should be predicted in advance to trigger the rejuvenation process to improve service availability. In this work, the k-nearest neighbor (k-NN) algorithm-based new approach has been used to identify the virtual machine's status, and a prediction of resource exhaustion time has been made. The proposed prediction model uses static thresholding and adaptive thresholding methods. The performance of the algorithms is compared, and it is found that for classification, the k-NN performs comparatively better, i.e., k-NN showed an accuracy of 97.6. In contrast, its counterparts performed with an accuracy of 96.0 (naïve Bayes) and 92.8 (decision tree). The comparison of the proposed work with previous similar works has also been discussed.
- Subjects
VIRTUAL machine systems; K-nearest neighbor classification; COMPUTER software; DECISION trees; THRESHOLDING algorithms
- Publication
International Journal of Electrical & Computer Engineering (2088-8708), 2023, Vol 13, Issue 2, p1773
- ISSN
2088-8708
- Publication type
Article
- DOI
10.11591/ijece.v13i2.pp1773-1781