移动社交网络中基于用户动态需求的D2D数据分流方法

Device-to-device Assisted Traffic Offloading Based on Users′Dynamic Content Demands

针对因数据流量的爆炸式增长给蜂窝网络带来的流量负担和网络拥塞等问题,提出一种基于移动社交网络中用户动态需求的D2D数据分流方法。考虑用户在一天中不同时段的兴趣和移动轨迹,构建用于描述用户流量需求的图结构。通过Newman快速算法将移动用户划分为不同的社团,同一社团中的用户具有相似的数据需求并且经常彼此联系。在此情况下,每个社团挑选不同的种子用户进行数据共享。为了最大化蜂窝网络的数据分流,对比五种不同的中心性度量方法选择种子节点,采用对比实验,证明新提出的DDS方案的有效性。实验结果表明,在DDS策略中,PageRank度量方法选择的种子节点分流表现最好。

Aiming at the traffic burden and network congestion caused by the explosive growth of data traffic to cellular networks,a D2D data off loading method based on the dynamic needs of users in mobile social networks is proposed.Such strategy considers users′interests and mobility trace in different time periods of a day,on which a graph structure is constructed for describing users′traffic demand.The Newman fast algorithm divides mobile users into different communities.Users in the same community have similar data needs and often contact each other.Under such situation,seed users in each community are selected for data sharing.Compare five different centrality measurement methods to select seed nodes,and use comparative experiments to prove the effectiveness of the newly proposed DDS scheme.The experimental results show that in the DDS strategy,the seed node shunt selected by the Page Rank measurement method performs best.