I-Corps: AdsProphet: Full-screen Delay-aware Mobile Ads Display

移动广告是一个巨大且快速增长的市场，其驱动因素是观看流量和广告资金从其他媒体转移到移动设备。2014年，全球移动广告支出约为400亿美元，预计2019年将超过近2000亿美元。在目前运营的数十万应用开发商中，90%的开发商提供免费应用，通过“应用内”广告创收：当用户点击应用内嵌入的广告时，开发商就能获得报酬。如今，这些应用开发商不得不在他们的应用中播放横幅广告，这是一种通常在屏幕底部运行的小型广告形式，吸引的用户注意力很少，从而减少了开发商的收益。提出的技术“AdsProphet”是一种新颖的移动广告库，它是基于用户在使用应用程序时，大量时间浪费在等待应用程序加载远程数据上，而这种“冻结时间”没有得到充分利用。AdsProphet可以找到这些有价值的窗口，并显示全屏广告，吸引用户的注意力比横幅广告高25倍。I-Corps团队假设应用开发者可以使用AdsProphet以横幅广告10%的比例显示全屏广告，那么AdsProphet有望在不影响用户体验的情况下使开发者的收益翻倍。AdsProphet背后的关键技术是一种新型的移动设备实时用户感知延迟预测系统。提出这样一个系统是具有挑战性的：首先，在每次网络延迟期间，只有一部分是用户感知的延迟，此时用户只能等待。在任何系统中都没有针对它的内置事件。这个I-Corps团队提出了一种新颖的方法，通过结合网络行为操纵技术、图像相似性比较算法和用户行为模型，能够智能地检测用户感知的延迟。其次，移动设备上的网络条件变化巨大且频繁：用户将他们的手机从一个地方移动到另一个地方，并且一直连接到不同的网络，例如WIFI或蜂窝网络。此外，预测过程必须决定是否实时播放广告；否则，它会浪费时间去播放全屏广告并影响开发者？收入。该团队首先提出了一种预测用户感知延迟的方法，通过设计一种新的算法来有效地估计带宽以及到目标服务器的往返时间，这两者都是当前网络状况的最基本指标。然后，为了进一步加速所提出的预测系统，该团队提出了基于用户历史的网络历史模型。

Mobile advertising is a large and quickly growing market, driven by the movement of viewing traffic and advertising dollars from other media to mobile. In 2014, mobile worldwide ad spending is about $40 billion and it's expected to top nearly $200 billion in 2019. Among all the hundreds of thousands of app developers operating today, 90% of which offer free apps that create revenues through "in-app" advertising: they get paid when a user clicks on an ad embedded in their apps. Nowadays, these app developers have to play banner ad in their apps, which is a small-sized ad form that usually runs at the bottom of the screen, attracting littler user attentionand thus reducing developers' revenues. The proposed technology "AdsProphet" is a novel mobile ads library that is based on the observation that when user using apps, a lot of time has been wasted on waiting for the app to load remote data and such 'freezing time' has not been fully taken advantage of. AdsProphet can find these valuable windows and displays full-screen ads, which attracts user attention 25 times higher than what banner ads can achieve. This I-Corps team assumes app developers can use AdsProphet to display full-screen ads at a rate of 10% of banner ads, then AdsProphet is expected to double developers' revenue without affecting user experiences.The key technique behind AdsProphet is a novel real-time user-perceived delay prediction system on mobile device. It's challenging to propose such a system: first, during each networking delay,only a portion of it is user-perceived delay when user can do nothing but to wait. There is no built-in event for it in any systems. This I-Corps team proposes a novel approach that is able to intelligentlydetect user-perceived delay by combing techniques of network behavior manipulation, image similarity comparison algorithms and user behavior model. Second, the networking condition varies dramatically and frequently on a mobile device: users move their phones from place to place and connect to different networks such as WIFI or cellular network all the time. Moreover, the prediction process must decide whether or not to play ads in real-time; otherwise, it wastes the time to play full-screen ads and affect developers? revenues. The team first proposes an approach to predict user-perceived delay by designing a novel algorithm to efficiently estimate bandwidth aswell as round trip time to target servers, both of which serve as the most essential indicators of current networking condition. Then, to further accelerate the proposed prediction system, the team proposes a networking history model based on user's history.