تقرير
Enabling Long-term Fairness in Dynamic Resource Allocation
| العنوان: | Enabling Long-term Fairness in Dynamic Resource Allocation |
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| المؤلفون: | Si-Salem, T., Iosifidis, G., Neglia, G. |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Science and Game Theory, Computer Science - Multiagent Systems, Computer Science - Performance |
| الوصف: | We study the fairness of dynamic resource allocation problem under the $\alpha$-fairness criterion. We recognize two different fairness objectives that naturally arise in this problem: the well-understood slot-fairness objective that aims to ensure fairness at every timeslot, and the less explored horizon-fairness objective that aims to ensure fairness across utilities accumulated over a time horizon. We argue that horizon-fairness comes at a lower price in terms of social welfare. We study horizon-fairness with the regret as a performance metric and show that vanishing regret cannot be achieved in presence of an unrestricted adversary. We propose restrictions on the adversary's capabilities corresponding to realistic scenarios and an online policy that indeed guarantees vanishing regret under these restrictions. We demonstrate the applicability of the proposed fairness framework to a representative resource management problem considering a virtualized caching system where different caches cooperate to serve content requests. Comment: Accepted to ACM SIGMETRICS 2023 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1145/3570606 |
| URL الوصول: | http://arxiv.org/abs/2208.05898 |
| رقم الأكسشن: | edsarx.2208.05898 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1145/3570606 |
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