[private-measurement] Evaluating off-device attribution proposals at larger scales (#21)

saxena-shobhit has just created a new issue for https://github.com/patcg/private-measurement:

== Evaluating off-device attribution proposals at larger scales ==
Off-device attribution is an interesting direction to explore for advertising attribution. It is important that the proposals in this space meet the scalability requirements of the real world traffic loads, however. The current scale at which these proposals (such as the [Interoperable Private Attribution](https://github.com/patcg-individual-drafts/ipa/blob/main/IPA-End-to-End.md)) have been [evaluated](https://github.com/patcg/meetings/blob/main/2022/08/09-telecon/IPA-August-2022-Update-PATCG-Issue-70.pdf) so far seems to be at the lower end of real world traffic loads. We want to better understand the scalability characteristics of these off-device attribution proposals.

We propose that the off-device attribution proposals be evaluated at the following ad-event volume scales: 10M, 100M, 1B, 10B, 100B. This would help in understanding the performance for advertisers of various sizes, supporting queries which span across multiple advertisers and supporting queries across wider date ranges. For the evaluation, ad-event and unattributed conversion trigger volumes should be considered to be at an identical order of magnitude (i.e. at the high end, tests of 100B ad events and 100B conversions).

Please view or discuss this issue at https://github.com/patcg/private-measurement/issues/21 using your GitHub account


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Received on Friday, 3 February 2023 00:40:10 UTC