SGER: The CogNet (Cognitive Complete Knowledge Network) System

SGER：CogNet（认知完整知识网络）系统奖0650048 Ramesh Rao认知完整知识网络（CogNet）系统结合了存储、网络连接和设备功能方面的进步，以及分析方法方面的进步，使下一代无线系统在部署的整个生命周期内都能改善其性能。CogNet架构利用低成本的“某时某地”通信的可用性，通过将用户、设备甚至整个网络作为探测器来异步和自动地收集大量用户数据。收集的信息来自无线电状态、网络状态、环境状态和用户配置文件，并在时空上标记和存档在分布式存储库中，并提供给参与者社区。特定时空区域的用户可以通过查询该存储库来了解典型的使用情况、其他人的体验、网络状况和协议参数，并调整或调整自己以达到期望的服务质量。我们使用随机分析、算法开发、性能分析和优化以及原型部署来从任何移动终端内产生的大量内部状态数据中识别全局相关的内部状态数据;管理数据传输和存档;设计学习模型和算法以适应大型和多样化的收集数据集;开发跨层、跨系统的适应性以使用从集体经验中获得的信息;以及分析和学习网络流量和网络参数以识别适当的服务组合参数以保证用户体验。

SGER: CogNet (Cognitive Complete Knowledge Network) SystemAward 0650048Ramesh RaoThe Cognitive Complete Knowledge Network (CogNet) system combines advances in storage, network connectivity, and device capability, with advances in analytical approaches to make next generation wireless systems refine their performance throughout the lifetime of theirdeployment. The CogNet architecture exploits the availability of low cost "some time some where" communications to asynchronously and automatically gather large amounts of user data by enlisting users, devices, and even the whole network as probes. The information gatheredis derived from the radio state, network state, environment state, and user profiles, and is spatio-temporally tagged and archived in a distributed repository and made available to the community of participants. A user in a particular spatio-temporal region could learnabout typical usage, others' experiences, network conditions, and protocol parameters by querying this repository and tune or adapt itself to achieve the desired quality of service.We use stochastic analysis, algorithm development, performance analysis and optimization, and prototype deployment to identify globally relevant internal state data from the vast amounts generated within any mobile device; manage data transfer and archiving; design learning models and algorithms to fit the large and diverse collected dataset; develop cross-layer, cross-system adaptations to use information obtained from the collective experience; and analyze and learn the network traffic and network parameters to identify appropriate service compositioning parameters to guarantee user experience.