Ad Serving Using a Compact Allocation Plan

TL;DR

This paper introduces a compact, offline-computed allocation plan for guaranteed delivery ad serving that is efficient, scalable, and suitable for real-time, distributed online ad serving environments.

Contribution

The paper proposes a novel compact allocation plan approach that is small, stateless, and effective for large-scale guaranteed ad delivery, addressing key challenges in the field.

Findings

Plans are small, using only O(1) space per contract.

The approach is effective on real datasets.

Supports distributed ad serving without central coordination.

Abstract

A large fraction of online display advertising is sold via guaranteed contracts: a publisher guarantees to the advertiser a certain number of user visits satisfying the targeting predicates of the contract. The publisher is then tasked with solving the ad serving problem - given a user visit, which of the thousands of matching contracts should be displayed, so that by the expiration time every contract has obtained the requisite number of user visits. The challenges of the problem come from (1) the sheer size of the problem being solved, with tens of thousands of contracts and billions of user visits, (2) the unpredictability of user behavior, since these contracts are sold months ahead of time, when only a forecast of user visits is available and (3) the minute amount of resources available online, as an ad server must respond with a matching contract in a fraction of a second. We present a solution to the guaranteed delivery ad serving problem using {\em compact allocation plans}. These plans, computed offline, can be efficiently queried by the ad server during an ad call; they are small, using only O(1) space for contract; and are stateless, allowing for distributed serving without any central coordination. We evaluate this approach on a real set of user visits and guaranteed contracts and show that the compact allocation plans are an effective way of solving the guaranteed delivery ad serving problem.