Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A significant fraction of the operational expenditures incurred by cloud service providers relates to their networking (Internet access) and electricity consumption. Both depend on the peak-demand over the billing interval. In the future, cloud services providers may in turn recoup these costs from their long-term customers through peak-based pricing. We explore two different methods for the cloud provider to recoup this charge: (i) equal allocation and (ii) proportional to usage allocation. Furthermore, we consider multiple strategic tenants whose active demand response to cloud price settings jointly depends on job responsiveness (modeled as queueing delay of admitted jobs) and lost/shed workload (due to excessive delay). Under certain conditions, we prove existence and uniqueness of Nash equilibria for regimes (i) and (ii). Due to nonconvexity in the utility (or cost) functions, existence statements require leveraging potentiality arguments while uniqueness statements rely on imposing further convexityrequirements. The resulting Nash equilibrium is parametrized by the price per unit demand, which may be strategically set by the cloud to maximize its revenue subject to tenants reaching a Nash equilibrium. We model the resulting interactions as a Stackelberg game between the cloud and a set of tenants. A relatively general existence statement is provided for the Stackelberg equilibrium under regime (i). For a special case of regime (ii), the unique Stackelberg equilibrium is characterized. Finally, we provide a numerical study for such a framework using real-world peak-based prices from an electric utility and demands given by Google workload traces.'

Original languageEnglish (US)
Title of host publicationProceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages244-254
Number of pages11
ISBN (Electronic)9781538627631
DOIs
StatePublished - Nov 13 2017
Event25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017 - Banff, Canada
Duration: Sep 20 2017Sep 22 2017

Publication series

NameProceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017

Other

Other25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017
CountryCanada
CityBanff
Period9/20/179/22/17

Fingerprint

Pricing
Electric utilities
Stackelberg Equilibrium
Nash Equilibrium
Cost functions
Costs
Electricity
Internet
Workload
Stackelberg Game
Non-convexity
Queueing
Utility Function
Networking
Cost Function
Demand
Numerical Study
Existence and Uniqueness
Uniqueness
Customers

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Modeling and Simulation

Cite this

Kesidis, G., Shanbhag, U. V., Nasiriani, N., & Urgaonkar, B. (2017). Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response. In Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017 (pp. 244-254). [8107450] (Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MASCOTS.2017.24
Kesidis, George ; Shanbhag, Uday V. ; Nasiriani, Neda ; Urgaonkar, Bhuvan. / Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response. Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 244-254 (Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017).
@inproceedings{e081a610ea9f4941aab6049b067302e5,
title = "Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response",
abstract = "A significant fraction of the operational expenditures incurred by cloud service providers relates to their networking (Internet access) and electricity consumption. Both depend on the peak-demand over the billing interval. In the future, cloud services providers may in turn recoup these costs from their long-term customers through peak-based pricing. We explore two different methods for the cloud provider to recoup this charge: (i) equal allocation and (ii) proportional to usage allocation. Furthermore, we consider multiple strategic tenants whose active demand response to cloud price settings jointly depends on job responsiveness (modeled as queueing delay of admitted jobs) and lost/shed workload (due to excessive delay). Under certain conditions, we prove existence and uniqueness of Nash equilibria for regimes (i) and (ii). Due to nonconvexity in the utility (or cost) functions, existence statements require leveraging potentiality arguments while uniqueness statements rely on imposing further convexityrequirements. The resulting Nash equilibrium is parametrized by the price per unit demand, which may be strategically set by the cloud to maximize its revenue subject to tenants reaching a Nash equilibrium. We model the resulting interactions as a Stackelberg game between the cloud and a set of tenants. A relatively general existence statement is provided for the Stackelberg equilibrium under regime (i). For a special case of regime (ii), the unique Stackelberg equilibrium is characterized. Finally, we provide a numerical study for such a framework using real-world peak-based prices from an electric utility and demands given by Google workload traces.'",
author = "George Kesidis and Shanbhag, {Uday V.} and Neda Nasiriani and Bhuvan Urgaonkar",
year = "2017",
month = "11",
day = "13",
doi = "10.1109/MASCOTS.2017.24",
language = "English (US)",
series = "Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "244--254",
booktitle = "Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017",
address = "United States",

}

Kesidis, G, Shanbhag, UV, Nasiriani, N & Urgaonkar, B 2017, Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response. in Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017., 8107450, Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017, Institute of Electrical and Electronics Engineers Inc., pp. 244-254, 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017, Banff, Canada, 9/20/17. https://doi.org/10.1109/MASCOTS.2017.24

Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response. / Kesidis, George; Shanbhag, Uday V.; Nasiriani, Neda; Urgaonkar, Bhuvan.

Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 244-254 8107450 (Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response

AU - Kesidis, George

AU - Shanbhag, Uday V.

AU - Nasiriani, Neda

AU - Urgaonkar, Bhuvan

PY - 2017/11/13

Y1 - 2017/11/13

N2 - A significant fraction of the operational expenditures incurred by cloud service providers relates to their networking (Internet access) and electricity consumption. Both depend on the peak-demand over the billing interval. In the future, cloud services providers may in turn recoup these costs from their long-term customers through peak-based pricing. We explore two different methods for the cloud provider to recoup this charge: (i) equal allocation and (ii) proportional to usage allocation. Furthermore, we consider multiple strategic tenants whose active demand response to cloud price settings jointly depends on job responsiveness (modeled as queueing delay of admitted jobs) and lost/shed workload (due to excessive delay). Under certain conditions, we prove existence and uniqueness of Nash equilibria for regimes (i) and (ii). Due to nonconvexity in the utility (or cost) functions, existence statements require leveraging potentiality arguments while uniqueness statements rely on imposing further convexityrequirements. The resulting Nash equilibrium is parametrized by the price per unit demand, which may be strategically set by the cloud to maximize its revenue subject to tenants reaching a Nash equilibrium. We model the resulting interactions as a Stackelberg game between the cloud and a set of tenants. A relatively general existence statement is provided for the Stackelberg equilibrium under regime (i). For a special case of regime (ii), the unique Stackelberg equilibrium is characterized. Finally, we provide a numerical study for such a framework using real-world peak-based prices from an electric utility and demands given by Google workload traces.'

AB - A significant fraction of the operational expenditures incurred by cloud service providers relates to their networking (Internet access) and electricity consumption. Both depend on the peak-demand over the billing interval. In the future, cloud services providers may in turn recoup these costs from their long-term customers through peak-based pricing. We explore two different methods for the cloud provider to recoup this charge: (i) equal allocation and (ii) proportional to usage allocation. Furthermore, we consider multiple strategic tenants whose active demand response to cloud price settings jointly depends on job responsiveness (modeled as queueing delay of admitted jobs) and lost/shed workload (due to excessive delay). Under certain conditions, we prove existence and uniqueness of Nash equilibria for regimes (i) and (ii). Due to nonconvexity in the utility (or cost) functions, existence statements require leveraging potentiality arguments while uniqueness statements rely on imposing further convexityrequirements. The resulting Nash equilibrium is parametrized by the price per unit demand, which may be strategically set by the cloud to maximize its revenue subject to tenants reaching a Nash equilibrium. We model the resulting interactions as a Stackelberg game between the cloud and a set of tenants. A relatively general existence statement is provided for the Stackelberg equilibrium under regime (i). For a special case of regime (ii), the unique Stackelberg equilibrium is characterized. Finally, we provide a numerical study for such a framework using real-world peak-based prices from an electric utility and demands given by Google workload traces.'

UR - http://www.scopus.com/inward/record.url?scp=85040510827&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85040510827&partnerID=8YFLogxK

U2 - 10.1109/MASCOTS.2017.24

DO - 10.1109/MASCOTS.2017.24

M3 - Conference contribution

AN - SCOPUS:85040510827

T3 - Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017

SP - 244

EP - 254

BT - Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Kesidis G, Shanbhag UV, Nasiriani N, Urgaonkar B. Competition and Peak-Demand Pricing in Clouds under Tenants' Demand Response. In Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 244-254. 8107450. (Proceedings - 25th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2017). https://doi.org/10.1109/MASCOTS.2017.24