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Titel:

Online revenue maximization for server pricing.

Dokumenttyp:
Journal Article
Autor(en):
Boodaghians, Shant; Fusco, Federico; Leonardi, Stefano; Mansour, Yishay; Mehta, Ruta
Abstract:
Efficient and truthful mechanisms to price resources on servers/machines have been the subject of much work in recent years due to the importance of the cloud market. This paper considers revenue maximization in the online stochastic setting with non-preemptive jobs and a unit capacity server. One agent/job arrives at every time step, with parameters drawn from the underlying distribution. We design a posted-price mechanism which can be efficiently computed and is revenue-optimal in expectation...     »
Zeitschriftentitel:
Auton Agent Multi Agent Syst
Jahr:
2022
Band / Volume:
36
Heft / Issue:
1
Volltext / DOI:
doi:10.1007/s10458-022-09544-y
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/35125936
Print-ISSN:
1387-2532
TUM Einrichtung:
Institut für Allgemeine Pathologie und Pathologische Anatomie
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