Interest Aware PeopleRank: Towards Effective Social-Based Opportunistic Advertising

被引:0
作者
Al Ayyat, Soumaia [1 ]
Harras, Khaled A. [2 ]
Aly, Sherif G. [1 ]
机构
[1] Amer Univ Cairo, Comp Sci & Engn Dep, Cairo, Egypt
[2] Carnegie Mellon Univ Qatar, Sch Comp Sci, Doha, Qatar
来源
2013 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) | 2013年
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Various emerging context aware social-based applications and services assume constant non-disruptive connectivity. Mobile advertisers in such environments want to reach potentially interested users in a given proximity and within a specified short-duration, whether these users are connected to the network or not. While opportunistic forwarding algorithms can be leveraged for forwarding these advertisements, there is little incentive for those not interested in the ad to act as forwarders. Our goal in this paper is to leverage explicit interest, gathered from a user's social profile, and integrate it with social-based opportunistic forwarding algorithms in order to enable soft real-time opportunistic ad delivery in intermittently connected mobile networks. We propose IPeR, a fully distributed interest-aware forwarding algorithm that integrates with PeopleRank to reduce the overall cost and delay while reducing the number of contacted uninterested candidates. Our results, obtained via simulations and validated with real mobility traces coupled with user social data, are promising. In comparison to interest-oblivious socially-aware protocols such as PeopleRank, the IPeR approach reduces the cost to 70% to reach the same delivery ratio, and reduces the ratio of contacted uninterested forwarders by 23%. It also achieves an extra 70% recall and 107% accuracy with only 2% less precision.
引用
收藏
页码:4428 / 4433
页数:6
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