The unprecedented growth of wireless mobile traffic, mainly due to multimedia traffic over online social platforms has strained the resources in the mobile backhaul network. A promising approach to reduce the backhaul load is to proactively cache content at the network edge, taking into account the overlaid social network. Known caching schemes require complete knowledge of the social graph and mainly focus on one-to-one interactions forgoing the prevalent mode of content sharing among circles of 'friends'. We propose Bingo, a proactive content caching scheme that leverages the presence of interest groups in online social networks. The mobile network operator (MNO) can choose to incrementally deploy Bingo at select network nodes (base stations, packet core, data center) based on user profiles and revenue numbers. We approximate the group memberships of users using the available user-content request logs without any prior knowledge of the overlaid social graph. Bingo can cater to the evolving nature of online social groups and file popularity distribution for making caching decisions. We use synthetically generated group structures and simulate user requests at the base station for empirical evaluation against traditional and recent caching schemes. Bingo achieves up to 30%-34% gain over the best baseline.
翻译:无线移动交通史无前例的增长,主要由于网上社交平台的多媒体交通,使得移动回路网络的资源紧张。减少回路负荷的一个有希望的方法是主动地在网络边缘缓存内容,同时考虑到覆盖的社会网络。已知的缓冲计划需要完全了解社会图,并主要侧重于一对一的互动,以打破“朋友”圈间共享内容的流行模式。我们建议宾果,一个主动的内容缓存计划,利用在线社交网络中利益群体的存在。移动网络运营商(MNO)可以选择在基于用户概况和收入数字的选定网络节点(基地站、包芯、数据中心)逐步部署“Rigon”。我们使用现有的用户-连线请求日志来接近用户群体成员,而事先不了解过封路社会图的任何知识。宾果可以满足在线社会群体不断变化的性质变化,为做出缓存决定提供文件版面分布。我们使用合成组结构和模拟用户在基地站对传统和最近缓存计划进行实证性评估的请求,可以达到30%-34%的最高基线。