项目名称: 大数据的双重机会路由机制研究
项目编号: No.61472403
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 自动化技术、计算机技术
项目作者: 黄建辉
作者单位: 中国科学院计算技术研究所
项目金额: 80万元
中文摘要: 大数据所具有的体量超大、来源多样和价值低密等特点,使得单纯依靠传统网络无法满足其传输要求。作为传统网络的补充,移动机会认知无线网络(MOCRN)借助节点移动机会和频谱空闲机会,可发动海量终端的传输和计算潜力,并解决频谱资源利用低的问题,实现经济低碳的高效传输。然而,MOCRN中的数据传输同时受限于时域-空域-频域三维约束,给路由带来巨大的挑战。针对这种现状,本项目拟提出一套大数据的双重机会路由机制,重点研究:(1)双重动态随机耦合网络的信息传播模型;(2)面向多元异质服务对象的大数据双重机会路由策略;(3)大数据融合路由策略。其中,研究重点(1)从理论层面揭示MOCRN信息传播动力学特性,为设计高效的双重机会路由策略提供理论依据;研究重点(2)和(3)从实践层面上以(1)的理论成果为指导,面向大数据应用的异质传输服务对象及融合路由需求,在时域-空域-频域三维约束下,实现高效的大数据传输。
中文关键词: 机会路由;大数据;数据融合
英文摘要: Due to the traits of large-volume, multiple-source and low density of value, only using traditional networks cannot meet big data applications' transmission requirements. As a complementation, Mobile Opportunistic Cognitive Radio Networks (MOCRNs) employ the unused transmission and computing capacity of massive of mobile nodes, as well as the unused spectrum, to realize efficient transmission with low cost, by taking advantage of both nodes' movement opportunities and idle spectrum opportunities. However, owing to the temporal, spatial and spectrum restrictions, MOCRN's routing is a big challenge. To solve this problem, this project will propose a series of dual opportunistic routing mechanisms for big data applications, including: 1) the modeling of information dissemination in the dual dynamic stochastic coupled networks; 2) the dual opportunistic routing strategies for big data applications orienting multidimensional and heterogeneous transmission objectives; 3) the routing strategy with big data fusion. Among them, the content 1) reveals the information dissemination dynamic characteristic of MOCRN from the theoretical level, providing the theoretical basis for designing effective dual opportunistic routing strategies. The contents 2) and 3) design effective data transmission under the temporal, spatial and spectrum restrictions for meeting the requirements of the heterogeneous transmission objectives and routing with data fusion for big data applications.
英文关键词: opportunistic routing;big data;data fusion