流量更少效果更好：实时广告交易中的竞争感知请求调度
Less Traffic, Better Outcomes: Competition-Aware Request Dispatch in Real-Time Ad Exchanges
RTB请求转发太多？这篇论文用竞争感知调度砍掉34%流量，收入还涨4.6%，搞广告系统的朋友可以读读。
实时竞价（RTB）广告交易平台通常将几乎所有请求转发给需求方平台（DSP），但实际出价率很低。一项新研究提出竞争感知请求调度框架，利用分布性出价预测和概率转发，决定每个请求是否发送给每个DSP。
系统通过轻量策略优化动态调整每个DSP的阈值，适应市场变化。在日请求量超200亿的生产平台上的四轮在线实验中，全多DSP部署使DSP请求量降低34.
2%，净收入提升4.6%（p<0.
001）。
Less Traffic, Better Outcomes: Competition-Aware Request Dispatch in Real-Time Ad Exchanges
Real-time bidding (RTB) ad exchanges typically forward nearly all incoming requests to demand-side platforms (DSPs), even though only a small fraction receive bids. This over-distribution weakens auction outcomes: DSPs throttle participation under compute and budget constraints, reducing the effective use of limited bidding capacity. We present a competition-aware request dispatch framework that uses distributional bid prediction and probabilistic forwarding to decide whether each request should be sent to each DSP. The system adapts per-DSP thresholds over time through lightweight policy optimization to track non-stationary market conditions. We evaluate the framework through four sequential online experiments on a production platform serving over 20 billion daily requests. A full multi-DSP deployment reduces DSP request volume under the policy by 34.2% while increasing net revenue by 4.6% (p<0.001) in a recent 14-day window after an initial DSP adaptation period. Further analysis highlights strong heterogeneity across traffic segments and reveals that aggregate metrics can be misleading. Segment-level and per-DSP analyses suggest that the policy surfaces comparative advantages among DSPs, improving monetized outcomes without increasing overall request volume.
This report is categorized under AITOP's "Papers" desk. Key entities and technical topics under continuous tracking include 实时竞价, DSP, 请求调度, 广告系统.
Source attribution: curated from arXiv cs.AI (@Jonaid Shianifar, Blaz Mramor, Fangda Zou, Matthieu C. Martin, Xingsheng Guo, Zhihua Zhu, Rong Zhou, Bichen Shi).