TY - GEN
T1 - A Fair Share
T2 - Adjunct Proceedings of the 33 ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2025
AU - Krigman, Shai
AU - Dery, Lihi
AU - Grinshpoun, Tal
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/6/12
Y1 - 2025/6/12
N2 - When users with different preferences and entitlements compete for limited access to a shared resource, maximizing total utility can lead to significant disparities in how users are served. We examine this tension in the context of allocating satellite observation windows, where users differ in their willingness to pay or their contribution to the system. The goal is to schedule observations efficiently while promoting balanced, fair access among users. This challenge is amplified in settings where coordination is decentralized and users negotiate outcomes without a central authority. We propose a hybrid algorithm designed to balance fairness and efficiency in distributed scheduling. Our method produces allocations that retain high efficiency while reducing inequality. Although developed for satellite scheduling, the algorithm applies more broadly to decentralized systems where users with heterogeneous preferences share limited resources.
AB - When users with different preferences and entitlements compete for limited access to a shared resource, maximizing total utility can lead to significant disparities in how users are served. We examine this tension in the context of allocating satellite observation windows, where users differ in their willingness to pay or their contribution to the system. The goal is to schedule observations efficiently while promoting balanced, fair access among users. This challenge is amplified in settings where coordination is decentralized and users negotiate outcomes without a central authority. We propose a hybrid algorithm designed to balance fairness and efficiency in distributed scheduling. Our method produces allocations that retain high efficiency while reducing inequality. Although developed for satellite scheduling, the algorithm applies more broadly to decentralized systems where users with heterogeneous preferences share limited resources.
KW - Efficiency-fairness tradeoff
KW - distributed allocation
KW - fair allocation
UR - https://www.scopus.com/pages/publications/105011044085
U2 - 10.1145/3708319.3733708
DO - 10.1145/3708319.3733708
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:105011044085
T3 - UMAP 2025 - Adjunct Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization
SP - 245
EP - 248
BT - UMAP 2025 - Adjunct Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization
Y2 - 16 June 2025 through 19 June 2025
ER -