融合无线异构网络的信息为中心互联网信息传输系统关键技术研究

Future information network is developing toward an information centric architecture. Considering the enormous trend of future information network and the tremendous requirement to improve the Quality of Experience of high speed railway users, this project focuses intensively on the theory and key technologies of information centric Internet information delivery system with wireless heterogeneous networks integrated. Particularly, we aim to solve the problem of information element group awareness, cache predictive dissemination and resource cross-layer multi-dimensional adaptation. The research mainly includes the following aspects. Firstly, we aim to investigate the information element group naming modeling of wireless heterogeneous network users and the hybrid sensing mechanism of information element group. Secondly, our objective is to explore the information element group aggregation model based on element characteristics. And we aim to propose cache predictive dissemination algorithm, in which the caches are able to be cached and managed in advance based on information element group behavior. Thirdly, we aim to develop resource cross-layer multi-dimensional dynamic adaptation methods. The methods can adaptively adjust the information requesting rate based on wireless channel status. And they are able to perform the matching and comparing function between network and user requirements so that the cooperative transmission of multi-dimensional wireless heterogeneous networks can be achieved. Through solving the above problems, the improved transmission throughput and lower packet loss rate can be achieved. The wireless users are expected to have better Quality of Experience. Thereby, the research results of the project can bring high speed, convenience and ubiquitous information access for people who are traveling.

本项目从未来信息网络以信息为中心的发展趋势出发，以提升高速铁路用户通信体验为目标，深入研究融合无线异构通信网络的信息为中心互联网信息传输关键技术，重点解决信息元素群感知、缓存预测式分发以及资源跨层多维度适配的问题。研究主要包括：研究无线异构用户的请求信息元素群命名模型，以及能够感知异构网络信息元素群的混合感知机制；探索能够根据元素特征聚类的信息元素群聚合模型，以及缓存预测式分发机制，能够根据信息元素群特征进行缓存动态预测式部署管理；建立面向无线异构网络的资源跨层多维度动态适配机制，能够根据无线链路状态进行信息请求速率自适应调节，以及跨层多维度协同传输机制，能够根据网络和用户服务行为进行匹配和协同传输。 通过上述问题的研究，提高网络传输吞吐量，降低数据传输丢包率，提高无线用户的信息获取体验，为人们出行提供信息的高速、便捷、泛在获取。

项目从未来信息网络以信息为中心的发展趋势出发，以提升高速铁路用户通信体验为目标，深入研究融合无线异构通信网络的信息为中心互联网信息传输关键技术，重.点解决信息元素群感知、缓存预测式分发以及资源跨层多维度适配的问题。研究主要包括：.1）研究无线异构用户的请求信息元素群命名模型，以及能够感知异构网络信息元素群的混合感知机制，设计层次化映射查询系统，可以进行精确感知；.2）探索能够根据元素特征聚类的信息元素群聚合模型，以及缓存预测式分发机制，能够根据信息元素群特征进行缓存动态预测式部署管理；.3）建立面向无线异构网络的资源跨层多维度动态适配机制，能够根据无线链路状态进行信息请求速率自适应调节，以及跨层多维度协同传输机制，能够根据网络和用户服务行为进行匹配和协同传输。 .研究结果表明，所提出的机制可以有效提高网络传输吞吐量，降低数据传输丢包率，降低数据传输时延，提高无线用户的信息获取体验，为人们出行提供信息的高速、便捷、泛在获取。