主动虚拟网络管理预测：复杂性作为预测、优化和保证的框架
Active Virtual Network Management Prediction: Complexity as a Framework for Prediction, Optimization, and Assurance
摘要：
主动网络的研究提供了激励重新访问传统上被归类为不同的属性和特征的信息传输，如协议与服务，在更基本的水平，本文认为计算和通信的复杂性的混合。本文研究的特定服务是由主动虚拟网络管理预测启用的网络自预测。计算/通信通过Kolmogorov复杂性进行分析。其结果是一种机制，以了解和提高主动网络的性能，特别是主动虚拟网络管理预测。主动虚拟网络管理预测机制允许以算法和静态形式的各种状态的信息在用于网络管理的预测服务中被传输。这些结果一般适用于信息的算法传输。Kolmogorov复杂性被用作描述主动网络中算法压缩、复杂性和预测精度之间关系的理论，并通过实验进行了验证。最后，本文的结论与复杂性为基础的信息保障框架，试图采取整体的观点脆弱性分析。
英文摘要：
Research into active networking has provided the incentive to re-visit what has traditionally been classified as distinct properties and characteristics of information transfer such as protocol versus service; at a more fundamental level this paper considers the blending of computation and communication by means of complexity. The specific service examined in this paper is network self-prediction enabled by Active Virtual Network Management Prediction. Computation/communication is analyzed via Kolmogorov Complexity. The result is a mechanism to understand and improve the performance of active networking and Active Virtual Network Management Prediction in particular. The Active Virtual Network Management Prediction mechanism allows information, in various states of algorithmic and static form, to be transported in the service of prediction for network management. The results are generally applicable to algorithmic transmission of information. Kolmogorov Complexity is used and experimentally validated as a theory describing the relationship among algorithmic compression, complexity, and prediction accuracy within an active network. Finally, the paper concludes with a complexity-based framework for Information Assurance that attempts to take a holistic view of vulnerability analysis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
