异构移动网络中协作基站缓存的优化理论与技术研究

Along with the fast development of mobile Internet industry, 4G high-speed mobile networks are covering every corner in the world, and mobile users are generating more and more demands on mobile multimedia services which giving raise to the exponential explosively growing mobile traffic. Aiming to optimize mobile Internet and to evolve current network to next generation green and smart mobile network, in this project, we mainly focus on extending the content-centric/information-centric/named data networking concept from future Internet to mobile networks, by deploying the cooperative caching among cells with different kinds of communication ranges at the edge of heterogeneous mobile networks and the user preferential popular content will be stored in the base stations near the users for a certain time, and thus we will intensely research on the hierarchical cells cooperative caching optimization theory and technology framework of large-scale heterogeneous mobile networks. Considering the diversity characteristics of mobile users, content and network topology, we exploit the accurate traffic modeling and the relevant joint optimization solution to reduce the traffic loading sharply. In order to ensure the user service quality, we investigate the fairer optimization model according to the different mobile users’ service latency. We establish the real heterogeneous cooperative cell caching experimental platform and study the experimental measurement methods based on real dataset. We study the optimization utilize the software/hardware resource under the space and time dimension in mobile networks, aiming to reduce unnecessary transmissions and thus energy waste, and to improve the service of quality of mobile users and this project will provide the basic theory and technology support of efficient future mobile networks.

4G高速移动网络已在全球实现大范围覆盖，移动互联网产业蓬勃发展，人们对于移动服务的需求日益增长，于是移动网络面临着指数级爆增的流量负荷。为了高效的优化移动网络并逐步演变至下一代智能绿色的移动网络，本课题将专注于扩展内容中心未来网络概念，在异构移动网络边缘覆盖范围大小各异的微基站上部署协作缓存，将移动用户偏好的流行数据内容进行临时存储，从而深入研究针对大规模异构移动网络的多层级基站协作缓存优化理论与技术框架。针对移动用户、内容和网络的多样化属性，探索精准的流量建模及联合优化解法，以大幅度减少流量负载；针对多样化移动用户服务延迟，探索更公平的优化模型，确保用户服务质量；研究并架设真实的异构协作基站缓存实验平台原型，建立基于真实数据的实验测试方法。本课题研究通过在空间和时间维度充分利用网络软硬件资源，减少重复网络流量及能耗浪费，提升用户服务质量，为高效的未来移动网络提供基础理论依据和技术支撑。

近年来，移动通信技术不断升级，即时通讯、电子商务、移动支付等互联网 应用逐渐走进了人们的日常生活，移动流量也随之呈现爆炸式的突涨。相关研究 发现，移动流量中大多是重复传输的多媒体数据。为了解决这样的流量爆炸与重 复传输问题，一些研究者提出在移动网络边缘部署缓存，通过在基站等边缘设备 中缓存部分流行内容，在靠近用户的位置满足数据访问请求，从而避免重复传输 浪费过多的网络资源，并通过缩短传输时延来改善用户的体验。本课题首先提出 了异构移动网络协作基站缓存的网内网间的流量优化算法，解决了协作基站缓存 的流量优化问题;然后，本课题提出了针对多样化移动用户的服务延迟模型，并 提出了一种基于学习的协作缓存框架，从而解决了异构移动网络协作基站中用户 延迟优化问题;最终，本课题设计并研发了异构移动网络协作基站缓存实验平台， 并建立了基于真实数据的实验测试方法。本课题分别从空间和时间的维度充分考 虑了边缘缓存的资源优化问题，通过最大化缓存资源的利用率来减少移动流量的 传输并提升服务质量，为绿色的未来移动网络架构提供了基础理论和技术支撑。