Modeling, Monitoring, and Optimization of Cognitive Networks

该提案的目标是为认知网络建模、监控和优化中的基本问题建立变革性的新解决方案，对理论、算法和实现都有重大影响。其智力价值包括网络制图的新概念，作为提炼和总结“网络状态”的工具，用于网络管理。由此产生的网络监控整体方法提供了由过去（和驱动未来）测量和系统设计规范驱动的模块化和可扩展的统计表示。此外，它能够推断全球网络行为和协议设计的适应性，以增强网络的鲁棒性和服务质量。CR网络性能的显着改善将通过增加生动的描述的网络全局状态的模型，占固有的非有形连接的认知无线链路，和频谱共享层次结构所产生的干扰的挑战。更广泛的影响包括符合IEEE 802.22标准的认知无线电技术的进步，以及智能电网，监视，地理监测和机构网络。此外，所利用的基本工具的切实进展将使生物信息学、语音和图像压缩、社交网络的机器学习和数据挖掘以及新兴的智能电网通信网络协议受益。通过荣誉论文和高级设计项目，拟议的研究还将影响学生的培训，使他们在最先进的无线认知系统和网络优化科目中获得实践经验，而这些课程并没有完全提供。

The objective of this proposal is to establish transformative novel solutions to fundamental problems in cognitive network modeling, monitoring and optimization with significant impact to both theory, algorithms, and implementation. The intellectual merit comprises the novel concept of network cartography as the tool for distilling and summarizing the "network state" for the purpose of network management. The resultant holistic approach to network monitoring offers modular and scalable statistical representations driven by past (and driving future) measurements and system design specifications. Further, it enables inference of global network behavior and adaptation of protocol designs to enhance network robustness and quality-of-service. Dramatic improvements in CR network performance will be attained by augmenting the vivid description of the network global state with models that account for the intrinsic non-tangible connectivity of cognitive wireless links, and the interference challenges arising from spectrum sharing hierarchies. The broader impacts include advances of the IEEE 802.22 compliant cognitive radio technologies, and smart grid, surveillance, geo-monitoring, and institutional networks. Furthermore, tangible advances in the fundamental tools exploited will permeate benefits to bio-informatics, speech and image compression, machine learning and data mining for social networks, and the emerging smart grid communication network protocols. Through Honors Theses and Senior Design Projects, the proposed research will also impact student training with hands-on experience in state-of-the-art wireless cognitive systems and network optimization subjects that are not fully provided by coursework.