Autonomic Computing: Applications of Self-Healing Systems
Autonomic Computing: Applications of Self-Healing Systems
复制标题
自主计算：自我修复系统的应用
DOI：
10.1109/dese.2011.22
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
A. Taleb
中科院分区：
文献类型：
--
作者：
M. Al;D. Al;A. Hussain;A. Taleb
自主计算的主要目标是实现系统的自我管理，以提高系统运行的可靠性、稳定性和性能。该领域需要研究与复杂系统相关的一些问题，例如，自我意识系统，何时何地发生错误状态，系统稳定的知识，分析问题，在不需要人为干预的情况下使用不同的适应解决方案进行治疗计划。本文重点研究了自主计算中最重要的组成部分--自愈技术。自愈是一种旨在检测、分析和修复系统中现有故障的技术。所有这些阶段都是在实时系统中完成的。在这种方法中，系统能够执行重新配置动作，以便从永久性故障中恢复。此外，自我修复系统应该有能力修改自己的行为，以响应环境中的变化。递归神经网络已被提出并用于解决自我修复的主要挑战，如监测，解释，解决和适应。
Self -- Management systems are the main objective of Autonomic Computing (AC), and it is needed to increase the running system's reliability, stability, and performance. This field needs to investigate some issues related to complex systems such as, self-awareness system, when and where an error state occurs, knowledge for system stabilization, analyze the problem, healing plan with different solutions for adaptation without the need for human intervention. This paper focuses on self-healing which is the most important component of Autonomic Computing. Self-healing is a technique that aims to detect, analyze, and repair existing faults within the system. All of these phases are accomplished in real-time system. In this approach, the system is capable of performing a reconfiguration action in order to recover from a permanent fault. Moreover, self-healing system should have the ability to modify its own behavior in response to changes within the environment. Recursive neural network has been proposed and used to solve the main challenges of self-healing, such as monitoring, interpretation, resolution, and adaptation.