AdCell: Ad Allocation in Cellular Networks

TL;DR

This paper introduces AdCell, a novel targeted advertising policy for cellular networks that optimizes ad delivery based on customer location, time, and advertiser budgets, using approximation algorithms for online and offline scenarios.

Contribution

It presents a new model for location-based mobile advertising and develops approximation algorithms with constant competitive ratios for both online and offline versions.

Findings

Developed approximation algorithms with constant competitive ratios.

Modeled location-based advertising as a generalized online matching problem.

Extended previous models like AdWords and secretary problem to cellular network context.

Abstract

With more than four billion usage of cellular phones worldwide, mobile advertising has become an attractive alternative to online advertisements. In this paper, we propose a new targeted advertising policy for Wireless Service Providers (WSPs) via SMS or MMS- namely {\em AdCell}. In our model, a WSP charges the advertisers for showing their ads. Each advertiser has a valuation for specific types of customers in various times and locations and has a limit on the maximum available budget. Each query is in the form of time and location and is associated with one individual customer. In order to achieve a non-intrusive delivery, only a limited number of ads can be sent to each customer. Recently, new services have been introduced that offer location-based advertising over cellular network that fit in our model (e.g., ShopAlerts by AT&T) . We consider both online and offline version of the AdCell problem and develop approximation algorithms with constant competitive ratio. For the online version, we assume that the appearances of the queries follow a stochastic distribution and thus consider a Bayesian setting. Furthermore, queries may come from different distributions on different times. This model generalizes several previous advertising models such as online secretary problem \cite{HKP04}, online bipartite matching \cite{KVV90,FMMM09} and AdWords \cite{saberi05}. ...