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Fair Allocation Without Trade

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abstract

We consider the age-old problem of allocating items among different agents in a way that is efficient and fair. Two papers, by Dolev et al. and Ghodsi et al., have recently studied this problem in the context of computer systems. Both papers had similar models for agent preferences, but advocated different notions of fairness. We formalize both fairness notions in economic terms, extending them to apply to a larger family of utilities. Noting that in settings with such utilities efficiency is easily achieved in multiple ways, we study notions of fairness as criteria for choosing between different efficient allocations. Our technical results are algorithms for finding fair allocations corresponding to two fairness notions: Regarding the notion suggested by Ghodsi et al., we present a polynomial-time algorithm that computes an allocation for a general class of fairness notions, in which their notion is included. For the other, suggested by Dolev et al., we show that a competitive market equilibrium achieves the desired notion of fairness, thereby obtaining a polynomial-time algorithm that computes such a fair allocation and solving the main open problem raised by Dolev et al.

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cs.DC 1

years

2025 1

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CONDITIONAL 1

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representative citing papers

Autonomous Dominant Resource Fairness for Blockchain Ecosystems

cs.DC · 2025-07-22 · conditional · novelty 6.0

ADRF adapts the loop-free Precomputed Dominant Resource Fairness algorithm to Ethereum smart contracts using fixed-point arithmetic and epoch-based demand/claim transactions, with measured gas costs linear in the number of resource types.

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  • Autonomous Dominant Resource Fairness for Blockchain Ecosystems cs.DC · 2025-07-22 · conditional · none · ref 43 · internal anchor

    ADRF adapts the loop-free Precomputed Dominant Resource Fairness algorithm to Ethereum smart contracts using fixed-point arithmetic and epoch-based demand/claim transactions, with measured gas costs linear in the number of resource types.