A fuzzy neural network for web service selection aimed at dynamic software rejuvenation

被引：0
|
作者：
Kalantari K.R. [1 ]
Ebrahimnejad A. [2 ]
Motameni H. [3 ]
机构：
[1] Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol
[2] Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr
[3] Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari
来源：
Turk J Electr Eng Comput Sci | 2020年 / 5卷 / 2718-2734期
关键词：
Fuzzy neural network; Software aging; Software rejuvenation; Web service;
D O I：
10.3906/ELK-2001-33
中图分类号：
学科分类号：
摘要：
Software rejuvenation is an effective technique to counteract software aging in continuously running applications such as web service-based systems. In these systems, web services are allocated based on the requirements of receivers and the facilities of servers. One of the challenges while assigning web services is how to select appropriate server to reduce faults. In this paper, we propose dynamic software rejuvenation as a proactive fault-tolerance technique based on the neural fuzzy system. While considering a threshold for the rejuvenation of each web service, we completed the training based on the features of the service providers as well as the requirements of the receivers. The results of simulations revealed that our strategy can decrease the failure rate in comparison with state-of-the-art strategies and improve system availability in web services. © TÜBİTAK
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页码：2718 / 2734
页数：16
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