Recommendations are employed by Content Providers (CPs) of streaming services in order to boost user engagement and their revenues. Recent works suggest that nudging recommendations towards cached items can reduce operational costs in the caching networks, e.g., Content Delivery Networks (CDNs) or edge cache providers in future wireless networks. However, cache-friendly recommendations could deviate from users' tastes, and potentially affect the CP's revenues. Motivated by real-world business models, this work identifies the misalignment of the financial goals of the CP and the caching network provider, and presents a network-economic framework for recommendations. We propose a cooperation mechanism leveraging the Nash bargaining solution that allows the two entities to jointly design the recommendation policy. We consider different problem instances that vary on the extent these entities are willing to share their cost and revenue models, and propose two cooperative policies, CCR and DCR, that allow them to make decisions in a centralized or distributed way. In both cases, our solution guarantees reaching a fair and Pareto optimal allocation of the cooperation gains. Moreover, we discuss the extension of our framework towards caching decisions. A wealth of numerical experiments in realistic scenarios show the policies lead to significant gains for both entities.
翻译:内容提供商(CPs)对流流服务采用了建议,以促进用户的参与及其收入。最近的工作表明,对缓存项目提出新建议,可以降低缓存项目的运行成本,例如内容提供网络(CDNs)或未来无线网络的边端缓存提供商等缓存网络的运行成本,但方便缓存的建议可能偏离用户的口味,并有可能影响CP的收入。在现实世界商业模式的推动下,这项工作确定了CP和缓存网络提供商的财务目标的错配,并为建议提供了一个网络经济框架。我们提议了一个合作机制,利用纳什谈判解决方案,使两个实体能够联合设计建议政策。我们考虑了不同的情况,这些实体愿意分享成本和收入模式的程度各不相同,并提出了两项合作政策,即CCRR和DCR,允许它们以集中或分配的方式作出决定。在这两种情况下,我们的解决方案保证CP和缓存网络提供商的财政目标得到公平、最佳的合作收益分配。此外,我们讨论了将框架扩展至缓存决定的问题。在现实情景中,大量的数字实验显示了两个实体取得的结果。