Reliability is Blind: Collective Incentives for Decentralized Computing Marketplaces Without Individual Behavior Information

In decentralized cloud computing marketplaces, ensuring fair and efficient interactions among asset providers and end-users is crucial. A key concern is meeting agreed-upon service-level objectives like the service's reliability. In this decentralized context, traditional mechanisms often fail to address the complexity of task failures, due to limited available and trustworthy insights into these independent actors' individual behavior. This paper proposes a collective incentive mechanism that blindly punishes all involved parties when a task fails. Based on ruin theory, we show that Collective Incentives improve behavior in the marketplace by creating a disincentive for faults and misbehavior even when the parties at fault are unknown, in turn leading to a more robust marketplace. Simulations for small and large pools of marketplace assets show that Collective Incentives enable to meet or exceed a reliability target, i.e., the success-rate of tasks run using marketplace assets, by eventually discarding failure-prone assets while preserving reliable ones.

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Published
2025-04-08
DOI
https://doi.org/10.1109/edcc-c66476.2025.00048
Primary Topic
Auction Theory and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Reliability is Blind: Collective Incentives for Decentralized Computing Marketplaces Without Individual Behavior Information

Sonia Ben Mokhtar, Anthony Simonet-Boulogne, Matthieu Bettinger, Henry Marie Mont
Auction Theory and Applications
article

Reliability is Blind: Collective Incentives for Decentralized Computing Marketplaces Without Individual Behavior Information

Sonia Ben Mokhtar, Anthony Simonet-Boulogne, Matthieu Bettinger, Henry Marie Mont
article en

Abstract

In decentralized cloud computing marketplaces, ensuring fair and efficient interactions among asset providers and end-users is crucial. A key concern is meeting agreed-upon service-level objectives like the service's reliability. In this decentralized context, traditional mechanisms often fail to address the complexity of task failures, due to limited available and trustworthy insights into these independent actors' individual behavior. This paper proposes a collective incentive mechanism that blindly punishes all involved parties when a task fails. Based on ruin theory, we show that Collective Incentives improve behavior in the marketplace by creating a disincentive for faults and misbehavior even when the parties at fault are unknown, in turn leading to a more robust marketplace. Simulations for small and large pools of marketplace assets show that Collective Incentives enable to meet or exceed a reliability target, i.e., the success-rate of tasks run using marketplace assets, by eventually discarding failure-prone assets while preserving reliable ones.

Centre National de la Recherche Scientifique (FR), Laboratoire d'Informatique en Images et Systèmes d'Information (FR), Institut National des Sciences Appliquées de Lyon (FR)
Agence Nationale de la Recherche
Openalex Percentile: Top 72%
Auction Theory and Applications
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Reliability is Blind: Collective Incentives for Decentralized Computing Marketplaces Without Individual Behavior Information — Sonia Ben Mokhtar, Anthony Simonet-Boulogne, et al. · (2025) | TGRS Research Map | TGRS