Exploiting network effects in the provisioning of large scale systems Jayakrishnan Nair, Adam Wierman Computing & Mathematical Sciences California Institute of Technology {ujk,adamw}@caltech.edu CWI Amsterdam, The Netherlands Bert Zwart Bert.Zwart@cwi.nl Thirdly, users of online services today are highly delay sensitive [6]. Large delays (due to congestion) in accessing a service can adversely a ect the user perceived quality of the service, potentially leading to stagnation in usage growth for the service. The goal of this paper is to understand how the capacity provisioning decision for online services is in uenced by the interplay of the three factors discussed above. More speci cally, in this paper, we consider the problem of optimal capacity provisioning for a rm operating an advertising supported online service. We model both network e ects and congestion sensitivity of the user base, and analyze the number of servers the rm must provision to maximize its pro t as the volume of the user base (or the market size) scales to in nity. Our analysis reveals that as the market size becomes large, the pro t maximizing strategy for the service provider involves operating the service in heavy tra c, and still having almost the
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Exploiting network effects in the provisioning of large scale systems
Nair, Jayakrishnan; Wierman, Adam; Zwart, Bert
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 39 (2)
Association for Computing Machinery – Sep 15, 2011
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