Addressing the complexity and scalability of autonomic

随着互联网规模的扩大，它面临着最初设计没有预见到的日益不利的环境。由于组件故障、人为操作错误、软件病毒传播和恶意攻击，故障已成为常态，而不是例外。在这种环境下，自动化网络管理技术将变得越来越重要，包括自主、自配置和自优化的设备和系统以及自保护和自愈的体系结构。配置模块是自主网络的核心功能，将被设计为将命令和文件或记录转换为抽象结构，进行配置，使用抽象结构提供的组合规则根据基于策略的目标添加或激活服务，并将配置结果重新转换为命令和配置文件。这些功能目前还不可用，仅以纯文本命令和文件的形式实现。包括服务、策略、功能和版本特征在内的配置信息将由称为构造的结构化树形拓扑表示，该构造可以使用具有形式合成操作的特定代数来操纵。我们的方法首先在于基于配置逻辑和形式编排约束扩展数学模型，使得能够通过操纵代数来验证配置信息。我们还将使用性能模拟来分析不同的自我配置场景，以评估自我优化、自我修复和自我保护的能力。性能分析将确定各种自主配置方案的影响。最后，我们计划试验自主网络的实现，并演示其在未来系统中的适用性。

As the Internet grows in scale, it faces an increasingly adverse environment that the original design did not envision. Faults have become the norm rather than the exception, due to component failures, human operational errors, spreads of software viruses, and malicious attacks. In this environment, automated network management techniques, including autonomic, self-configuring and self-optimizing devices and systems as well as self-protecting and self-healing architectures will become increasingly important.The research will focus on the developing the architecture of the configuration module for autonomic networks. The configuration module, - the core capability of an autonomic network -, will be designed to translate the commands and the files or records into abstract structures, does the configuration, adds or activates services according to policy-based goals using the rules of composition provided by the abstract structures and reconvert the configuration result into commands and configuration files. These features are not available today and are merely implemented in form of text-only commands and files. The configuration information including services, policies, functional and version features will be represented by structured tree-like topologies called "constructs" that can be manipulated using a specific algebra with formal composition operations.Our methodology consists first in extending the mathematical model based on configuration logic and formal orchestration constraints enabling the verification of the configuration information through the manipulation of the algebra. We will also use performance simulation to analyze different self-configuration scenarios to assess the self-optimizing, self-healing and self-protecting capabilities. The performance analysis will determine the impacts for various autonomic configuration scenarios. Finally, we plan to experiment with autonomic network implementations and demonstrate its applicability in future systems.