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Autores principales: Médard, Muriel, Chitra, Tarun, Grundei, Moritz, Zouarhi, Sajida
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2603.20426
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author Médard, Muriel
Chitra, Tarun
Grundei, Moritz
Zouarhi, Sajida
author_facet Médard, Muriel
Chitra, Tarun
Grundei, Moritz
Zouarhi, Sajida
contents We study pricing mechanisms for low-latency payload delivery in settings where participant rewards depend on the time required to reconstruct a payload. In such environments, the decoding time distribution determines deadline-meeting probabilities and therefore bounds a participant's willingness to pay for additional delivery rate. Using a mean-field formulation, we derive price-rate bounds from simple stochastic arrival models and instantiate them for (i) unsharded transmission and (ii) sharded delivery under three regimes: uncoded sharding, fixed-rate erasure coding, and rateless coding. These bounds yield a comparative characterization of how symbol usefulness translates into economic value under deadline-driven utilities. We further analyze a two-lane service consisting of a base lane and a Random Linear Network Coding (RLNC) fast lane. In this turbo decoding setting, a receiver combines shards arriving via both lanes to minimize time to decode. Under a fixed base-lane price-rate pair and an aggregate rate constraint, we derive a fast-lane pricing bound and show how even modest additional RLNC rate can generate measurable utility gains, depending on the base-lane propagation regime. The framework extends naturally to stepwise reward schedules with multiple deadlines, and we illustrate its applicability on representative scenarios motivated by blockchain message dissemination and latency-sensitive competition.
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spellingShingle Pricing Innovation Under Latency Constraints: A Mean-Field Analysis of Coded Payload Delivery
Médard, Muriel
Chitra, Tarun
Grundei, Moritz
Zouarhi, Sajida
Information Theory
We study pricing mechanisms for low-latency payload delivery in settings where participant rewards depend on the time required to reconstruct a payload. In such environments, the decoding time distribution determines deadline-meeting probabilities and therefore bounds a participant's willingness to pay for additional delivery rate. Using a mean-field formulation, we derive price-rate bounds from simple stochastic arrival models and instantiate them for (i) unsharded transmission and (ii) sharded delivery under three regimes: uncoded sharding, fixed-rate erasure coding, and rateless coding. These bounds yield a comparative characterization of how symbol usefulness translates into economic value under deadline-driven utilities. We further analyze a two-lane service consisting of a base lane and a Random Linear Network Coding (RLNC) fast lane. In this turbo decoding setting, a receiver combines shards arriving via both lanes to minimize time to decode. Under a fixed base-lane price-rate pair and an aggregate rate constraint, we derive a fast-lane pricing bound and show how even modest additional RLNC rate can generate measurable utility gains, depending on the base-lane propagation regime. The framework extends naturally to stepwise reward schedules with multiple deadlines, and we illustrate its applicability on representative scenarios motivated by blockchain message dissemination and latency-sensitive competition.
title Pricing Innovation Under Latency Constraints: A Mean-Field Analysis of Coded Payload Delivery
topic Information Theory
url https://arxiv.org/abs/2603.20426