Article

Optimal capacity planning in stochastic loss networks with time-varying workloads

Authors:

Sandeep Bhadra,

Mark S. SquillanteAuthors Info & Claims

SIGMETRICS '07: Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems

Pages 227 - 238

https://doi.org/10.1145/1254882.1254909

Published: 12 June 2007 Publication History

Abstract

We consider a capacity planning optimization problem in a general theoretical framework that extends the classical Erlang loss modeland related stochastic loss networks to support time-varying workloads. The time horizon consists of a sequence of coarse time intervals, each of which involves a stochastic loss network under a fixed multi-class workload that can change in a general manner from one interval to the next. The optimization problem consists of determining the capacities for each time interval that maximize a utility function over the entire time horizon, finite or infinite, where rewards gained from servicing customers are offset by penalties associated with deploying capacities in an interval and with changing capacities among intervals. We derive a state-dependent optimal policy within the context of a particular limiting regime of the optimization problem, and we prove this solution to be a symptotically optimal. Then, under fairly mild conditions, we prove that a similar structural property holds for the optimal solution of the original stochastic optimization problem, and we show how the optimal capacities comprising this solution can be efficiently computed.

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Jung KLu YShah DSharma MSquillante M(2019)Revisiting Stochastic Loss Networks: Structures and ApproximationsMathematics of Operations Research10.1287/moor.2018.0949Online publication date: 21-May-2019
https://doi.org/10.1287/moor.2018.0949
Li J(2016)Optimal resource capacity management for stochastic loss network systems with applications in clouds and data centers2016 IEEE 55th Conference on Decision and Control (CDC)10.1109/CDC.2016.7799095(5384-5389)Online publication date: Dec-2016
https://doi.org/10.1109/CDC.2016.7799095
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Published In

cover image ACM Conferences

SIGMETRICS '07: Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems

June 2007

398 pages

ISBN:9781595936394

DOI:10.1145/1254882

General Chair:
Leana Golubchik
University of Southern California, USA
,
Program Chairs:
Mostafa Ammar
Georgia Institute of Technology, USA
,
Mor Harchol-Balter
Carnegie Mellon University, USA

ACM SIGMETRICS Performance Evaluation Review Volume 35, Issue 1
SIGMETRICS '07 Conference Proceedings
June 2007
382 pages
ISSN:0163-5999
DOI:10.1145/1269899
Issue’s Table of Contents

Copyright © 2007 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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Published: 12 June 2007

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SIGMETRICS07: ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems

June 12 - 16, 2007

California, San Diego, USA

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Overall Acceptance Rate 459 of 2,691 submissions, 17%

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Cited By

Jung KLu YShah DSharma MSquillante M(2019)Revisiting Stochastic Loss Networks: Structures and ApproximationsMathematics of Operations Research10.1287/moor.2018.0949Online publication date: 21-May-2019
https://doi.org/10.1287/moor.2018.0949
Li J(2016)Optimal resource capacity management for stochastic loss network systems with applications in clouds and data centers2016 IEEE 55th Conference on Decision and Control (CDC)10.1109/CDC.2016.7799095(5384-5389)Online publication date: Dec-2016
https://doi.org/10.1109/CDC.2016.7799095
Tan YXia C(2015)An Adaptive Learning Approach for Efficient Resource Provisioning in Cloud ServicesACM SIGMETRICS Performance Evaluation Review10.1145/2788402.278840542:4(3-11)Online publication date: 2-Jun-2015
https://dl.acm.org/doi/10.1145/2788402.2788405
Lu YSharma MSquillante M(2014)Workforce management: Risk-based financial planning and capacity provisioningIBM Journal of Research and Development10.1147/JRD.2014.232770958:4(8:1-8:10)Online publication date: Jul-2014
https://doi.org/10.1147/JRD.2014.2327709
Zhang BPang GZwart B(2014)Refining piecewise stationary approximation for a Markov-regulated fluid queueACM SIGMETRICS Performance Evaluation Review10.1145/2667522.266752642:2(15-17)Online publication date: 4-Sep-2014
https://dl.acm.org/doi/10.1145/2667522.2667526
Tan YLu YXia C(2012)Provisioning for large scale loss network systems with applications in cloud computingACM SIGMETRICS Performance Evaluation Review10.1145/2425248.242527040:3(83-85)Online publication date: 4-Jan-2012
https://dl.acm.org/doi/10.1145/2425248.2425270
Kurve APang GKesidis Gde Veciana G(2012)Decentralized capacity reallocation for a loss network2012 46th Annual Conference on Information Sciences and Systems (CISS)10.1109/CISS.2012.6310748(1-5)Online publication date: Mar-2012
https://doi.org/10.1109/CISS.2012.6310748
Cao HHu JJiang CKumar TLi TLiu YLu YMahatma SMojsilović ASharma MSquillante MYu Y(2011)OnTheMarkInterfaces10.1287/inte.1110.059641:5(414-435)Online publication date: 1-Sep-2011
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Mojsilović AConnors D(2010)Workforce Analytics for the Services EconomyHandbook of Service Science10.1007/978-1-4419-1628-0_19(437-460)Online publication date: 22-Mar-2010
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Jung KLu YShah DSharma MSquillante M(2008)Revisiting stochastic loss networksACM SIGMETRICS Performance Evaluation Review10.1145/1384529.137550336:1(407-418)Online publication date: 2-Jun-2008
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