Article

On maximizing service-level-agreement profits

Authors:

Mark S. Squillante,

Joel L. WolfAuthors Info & Claims

EC '01: Proceedings of the 3rd ACM conference on Electronic Commerce

Pages 213 - 223

https://doi.org/10.1145/501158.501185

Published: 14 October 2001 Publication History

Abstract

We present a methodology for maximizing profits in a general class of e-commerce environments. The cost model is based on revenues that are generated when Quality-of-Service (QoS) guarantees are satisfied and on penalties that are incurred otherwise. The corresponding QoS criteria are derived from multiclass Service-Level-Agreements (SLAs) between service providers and their clients, which include the tail distributions of the per-class delays in addition to more standard QoS metrics such as throughput and mean delays. Our approach consists of formulating the optimization problem as a network flow model with a separable set of concave objective functions based on queueing-theoretic formulas, where the SLA classes are taken into account in both the constraints and the objective function. This problem is then solved via a fixed-point iteration. Numerous experiments illustrate the benefits of our approach.

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On maximizing service-level-agreement profits
1. Applied computing

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Published In

cover image ACM Conferences

EC '01: Proceedings of the 3rd ACM conference on Electronic Commerce

October 2001

277 pages

ISBN:1581133871

DOI:10.1145/501158

Conference Chairs:
Michael P. Wellman
University of Michigan
,
Yoav Shoham
Stanford University

Copyright � 2001 ACM.

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]

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SIGecom: Special Interest Group on Economics and Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 October 2001

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EC01: Third ACM Conference on Electronic Commerce

October 14 - 17, 2001

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EC '01 Paper Acceptance Rate 35 of 100 submissions, 35%;

Overall Acceptance Rate 664 of 2,389 submissions, 28%

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Cited By

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https://doi.org/10.1109/TCC.2018.2875443
Ma JLeung YKamath M(2019)Service System Design Under Information UncertaintyService Science10.1287/serv.2018.023411:1(40-56)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1287/serv.2018.0234
Hyytiä ERighter RBilenne OWu X(2018)Dispatching Discrete-Size Jobs with Multiple Deadlines to Parallel Heterogeneous ServersSystems Modeling: Methodologies and Tools10.1007/978-3-319-92378-9_3(29-46)Online publication date: 17-Oct-2018
https://doi.org/10.1007/978-3-319-92378-9_3
Kim MPons-Moll GPujades SBang SKim JBlack MLee S(2017)Data-driven physics for human soft tissue animationACM Transactions on Graphics10.1145/3072959.307368536:4(1-12)Online publication date: 20-Jul-2017
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Xu HBarbič J(2017)Example-based damping designACM Transactions on Graphics10.1145/3072959.307363136:4(1-14)Online publication date: 20-Jul-2017
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Zhao PLin XWang YChen SPedram M(2017)Hierarchical resource allocation and consolidation framework in a multi‐core server cluster using a Markov decision process modelIET Cyber-Physical Systems: Theory & Applications10.1049/iet-cps.2017.00602:3(118-126)Online publication date: 30-Oct-2017
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Feng GBuyya R(2016)Maximum revenue-oriented resource allocation in cloudInternational Journal of Grid and Utility Computing10.1504/IJGUC.2016.0737727:1(12-21)Online publication date: 1-Dec-2016
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Franke UBuschle M(2016)Experimental Evidence on Decision-Making in Availability Service Level AgreementsIEEE Transactions on Network and Service Management10.1109/TNSM.2015.251008013:1(58-70)Online publication date: 9-Mar-2016
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