Paper Info
Title
Revenue Maximization for Cloud Computing Services
Abstract
We study a stylized revenue maximization problem for a provider of cloud computing services, where the service provider (SP) operates an infinite capacity system in a market with heterogeneous customers with respect to their valuation and congestion sensitivity. The SP offers two service options: one with guaranteed service availability, and one where users bid for resource availability and only the “winning” bids at any point in time get access to the service. We show that even though capacity is unlimited, in several settings, depending on the relation between valuation and congestion sensitivity, the revenue maximizing service provider will choose to make the spot service option stochastically unavailable. This form of intentional service degradation is optimal in settings where user valuation per unit time increases sub-linearly with respect to their congestion sensitivity (i.e., their disutility per unit time when the service is unavailable) – this is a form of “damaged goods.” We provide some data evidence based on the analysis of price traces from the biggest cloud service provider, Amazon Web Services.
Year
DOI
Venue
2015
10.1145/2847220.2847245
SIGMETRICS Performance Evaluation Review
DocType
Volume
Issue
Journal
43
3
ISSN
Citations 
PageRank 
0163-5999
2
0.45
References 
Authors
7
2
Name
Order
Citations
PageRank
Cinar Kilcioglu120.45
Costis Maglaras210912.50