@inproceedings{318bd26ac9b640b3b36833badcc7c9c0,
title = "Incentivizing self-capping to increase cloud utilization",
abstract = "Cloud Infrastructure as a Service (IaaS) providers continually seek higher resource utilization to better amortize capital costs. Higher utilization not only can enable higher proit for IaaS providers but also provides a mechanism to raise energy eiciency; therefore creating greener cloud services. Unfortunately, achieving high utilization is diicult mainly due to infrastructure providers needing to maintain spare capacity to service demand luctuations. Graceful degradation is a self-adaptation technique originally designed for constructing robust services that survive resource shortages. Previous work has shown that graceful degradation can also be used to improve resource utilization in the cloud by absorbing demand luctuations and reducing spare capacity. In this work, we build a system and pricing model that enables infrastructure providers to incentivize their tenants to use graceful degradation. By using graceful degradation with an appropriate pricing model, the infrastructure provider can realize higher resource utilization while simultaneously, its tenants can increase their proit. Our proposed solution is based on a hybrid model which guarantees both reserved and peak on-demand capacities over lexible periods. It also includes a global dynamic price pair for capacity which remains uniform during each tenant's Service Level Agreement (SLA) term. We evaluate our scheme using simulations based on real-world traces and also implement a prototype using RUBiS on the Xen hypervisor as an end-to-end demonstration. Our analysis shows that the proposed scheme never hurts a tenant's net proit, but can improve it by as much as 93%. Simultaneously, it can also improve the efective utilization of contracts from 42% to as high as 99%.",
keywords = "Cloud computing, Dynamic pricing, Economic incentives, IaaS, Pricing model, Resource management, SLA, Utilization",
author = "Mohammad Shahrad and Cristian Klein and Liang Zheng and Mung Chiang and Erik Elmroth and David Wentzlaff",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 2017 Symposium on Cloud Computing, SoCC 2017 ; Conference date: 24-09-2017 Through 27-09-2017",
year = "2017",
month = sep,
day = "24",
doi = "10.1145/3127479.3128611",
language = "English (US)",
series = "SoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing",
publisher = "Association for Computing Machinery, Inc",
pages = "52--65",
booktitle = "SoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing",
}