TY - JOUR
T1 - Effective capacity modulation as an explicit control knob for public cloud profitability
AU - Gupta, Aayush
AU - Chen, Lydia Y.
AU - Birke, Robert
AU - Wang, Cheng
AU - Urgaonkar, Bhuvan
AU - Kesidis, George
N1 - Funding Information:
This work is supported, in part, by the following: NSF CAREER award 0953541, NSF CNS 1228717 and 1116626, Swiss National Science Foundation (projects 407540 and 167266), and an IBM faculty award. Authors’ addresses: C. Wang, VMware R&D, 6500 Riverplace Blvd, Austin, TX, USA, 78730; email: wangcheng@ vmware.com; B. Urgaonkar and G. Kesidis, IST Building, Pennsylvania State University, University Park, PA, USA 16802; emails: {bhuvan, kesidis}@cse.psu.edu; A. Gupta, IBM Research-Almaden, 650 Harry Road, San Jose, CA, USA 95120-6099; email: [email protected]; L. Y. Chen and R. Birke, IBM Research-Zurich, Säumerstrasse 4, CH–8803 Rüschlikon, Switzerland; emails: {yic, bir}@zurich.ibm.com. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]. © 2018 ACM 1556-4665/2018/05-ART2 $15.00 https://doi.org/10.1145/3139291
Publisher Copyright:
© 2018 Association for Computing Machinery.All right reserved.
PY - 2018
Y1 - 2018
N2 - In this article, we explore the efficacy of dynamic effective capacity modulation (i.e., using virtualization techniques to offer lower resource capacity than that advertised by the cloud provider) as a control knob for a cloud provider's profit maximization complementing the more well-studied approach of dynamic pricing. In particular, our focus is on emerging cloud ecosystems wherein we expect tenants to modify their demands strategically in response to such modulation in effective capacity and prices. Toward this, we consider a simple model of a cloud provider that offers a single type of virtual machine to its tenants and devise a leader/follower game-based cloud control framework to capture the interactions between the provider and its tenants. We assume both parties employ myopic control and short-term predictions to reflect their operation under the high dynamism and poor predictability in such environments. Our evaluation using a combination of real data center traces and real-world benchmarks hosted on a prototype OpenStack-based cloud shows 10% to 30% profit improvement for a cloud provider compared with baselines that use static pricing and/or static effective capacity.
AB - In this article, we explore the efficacy of dynamic effective capacity modulation (i.e., using virtualization techniques to offer lower resource capacity than that advertised by the cloud provider) as a control knob for a cloud provider's profit maximization complementing the more well-studied approach of dynamic pricing. In particular, our focus is on emerging cloud ecosystems wherein we expect tenants to modify their demands strategically in response to such modulation in effective capacity and prices. Toward this, we consider a simple model of a cloud provider that offers a single type of virtual machine to its tenants and devise a leader/follower game-based cloud control framework to capture the interactions between the provider and its tenants. We assume both parties employ myopic control and short-term predictions to reflect their operation under the high dynamism and poor predictability in such environments. Our evaluation using a combination of real data center traces and real-world benchmarks hosted on a prototype OpenStack-based cloud shows 10% to 30% profit improvement for a cloud provider compared with baselines that use static pricing and/or static effective capacity.
UR - https://www.scopus.com/pages/publications/85064549366
UR - https://www.scopus.com/pages/publications/85064549366#tab=citedBy
U2 - 10.1145/3139291
DO - 10.1145/3139291
M3 - Article
AN - SCOPUS:85064549366
SN - 1556-4665
VL - 13
JO - ACM Transactions on Autonomous and Adaptive Systems
JF - ACM Transactions on Autonomous and Adaptive Systems
IS - 1
M1 - 2
ER -