提高服务器可用性以保证系统整体安全：一种基于故障预测的预防性维护方法
Increasing Server Availability for Overall System Security: A Preventive Maintenance Approach Based on Failure Prediction
摘要：
服务器可用性（SA）是衡量系统整体安全性的重要指标。重要的安全系统依赖于其托管服务器的可用性来提供关键的安全服务。这些服务器中的许多主要使用Apache服务器通过Web提供管理界面。本文研究了通过使用人工神经网络（ANN）来预测软件老化现象，从而提高服务器的可用性。在一个典型的长时间运行的软件系统（Web服务器）上收集和分析几个资源使用数据。在Apache Web服务器数据集上训练多层感知器前馈人工神经网络，通过单变量时间序列预测来预测未来的服务器资源耗尽。结果进行了基准对非参数统计技术，参数时间序列模型和经验建模技术在文献中报道。
英文摘要：
Server Availability (SA) is an important measure of overall systems security. Important security systems rely on the availability of their hosting servers to deliver critical security services. Many of these servers offer management interface through web mainly using an Apache server. This paper investigates the increase of Server Availability by the use of Artificial Neural Networks (ANN) to predict software aging phenomenon. Several resource usage data is collected and analyzed on a typical long-running software system (a web server). A Multi-Layer Perceptron feed forward Artificial Neural Network was trained on an Apache web server data-set to predict future server resource exhaustion through uni-variate time series forecasting. The results were benchmarked against those obtained from non-parametric statistical techniques, parametric time series models and empirical modeling techniques reported in the literature.
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