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Controlling the Variability of Capacity Allocations Using Service Deferrals

Ferragut, Andres and Paganini, Fernando and Wierman, Adam (2017) Controlling the Variability of Capacity Allocations Using Service Deferrals. ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 2 (3). Art. No. 15. ISSN 2376-3639. doi:10.1145/3086506.

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Ensuring predictability is a crucial goal for service systems. Traditionally, research has focused on designing systems that ensure predictable performance for service requests. Motivated by applications in cloud computing and electricity markets, this article focuses on a different form of predictability: predictable allocations of service capacity. The focus of the article is a new model where service capacity can be scaled dynamically and service deferrals (subject to deadline constraints) can be used to control the variability of the active service capacity. Four natural policies for the joint problem of scheduling and managing the active service capacity are considered. For each, the variability of service capacity and the likelihood of deadline misses are derived. Further, the paper illustrates how pricing can be used to provide incentives for jobs to reveal deadlines and thus enable the possibility of service deferral in systems where the flexibility of jobs is not known to the system a priori.

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Additional Information:© 2017 IEEE. Received November 2016; accepted April 2017. The research in this paper has been partially supported by IADB–Ministerio de Industria y Energıa–Uruguay ATN/KF 13883 UR (Component 3) and ANII–Uruguay under grant FSE_1_2014_1_102426. Additional funding for this work was provided by the NSF through grants CNS-1319820, CNS-1518941, and CPS-1545096 as part of the NSF/DHS/DOT/NASA/NIH Cyber-Physical Systems Program.
Funding AgencyGrant Number
Ministerio de Industria y EnergıaATN/KF 13883 UR (Component 3)
Agencia Nacional de Investigación e Innovación (ANII)FSE_1_2014_1_102426
Subject Keywords:Mathematics of computing → Queueing theory; Information systems → Data centers; Hardware → Smart grid; Scheduling, deadlines, service variability, incentives
Issue or Number:3
Record Number:CaltechAUTHORS:20170814-150846810
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Official Citation:Andres Ferragut, Fernando Paganini, and Adam Wierman. 2017. Controlling the Variability of Capacity Allocations Using Service Deferrals. ACM Trans. Model. Perform. Eval. Comput. Syst. 2, 3, Article 15 (August 2017), 27 pages. DOI:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:80379
Deposited By: Kristin Buxton
Deposited On:14 Aug 2017 22:18
Last Modified:15 Nov 2021 19:30

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