Strong stochastic convexity and its applications in parametric optimization of queueing systems

J. George Shanthikumar; David D. Yao

doi:10.1109/CDC.1988.194392

Strong stochastic convexity and its applications in parametric optimization of queueing systems

J. George Shanthikumar
, David D. Yao

Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal

1 Citation (Scopus)

Abstract

The authors establish the notion of strong stochastic convexity (SSCX), which implies stochastic convexity. They demonstrate that SSCX is a property exhibited by a wide range of random variables. They also show that SSCX is preserved under random mixture, random summation, and any increasing and convex operations that are applied to a set of independent random variables. Making use of the closure property of SSCX, the authors study GI/G/1 queues and tandem queues with general interarrival and service times and finite intermediate buffers. Applications of the SSCX property in the parametric optimization of such systems are also discussed.

Original language	English
Pages (from-to)	657-662
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/CDC.1988.194392
Publication status	Published - Dec 1988
Externally published	Yes
Event	Proceedings of the 27th IEEE Conference on Decision and Control - Austin, TX, USA Duration: 7 Dec 1988 → 9 Dec 1988

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title = "Strong stochastic convexity and its applications in parametric optimization of queueing systems",

abstract = "The authors establish the notion of strong stochastic convexity (SSCX), which implies stochastic convexity. They demonstrate that SSCX is a property exhibited by a wide range of random variables. They also show that SSCX is preserved under random mixture, random summation, and any increasing and convex operations that are applied to a set of independent random variables. Making use of the closure property of SSCX, the authors study GI/G/1 queues and tandem queues with general interarrival and service times and finite intermediate buffers. Applications of the SSCX property in the parametric optimization of such systems are also discussed.",

author = "Shanthikumar, \{J. George\} and Yao, \{David D.\}",

year = "1988",

month = dec,

doi = "10.1109/CDC.1988.194392",

language = "English",

pages = "657--662",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

publisher = "IEEE",

note = "Proceedings of the 27th IEEE Conference on Decision and Control ; Conference date: 07-12-1988 Through 09-12-1988",

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TY - JOUR

T1 - Strong stochastic convexity and its applications in parametric optimization of queueing systems

AU - Shanthikumar, J. George

AU - Yao, David D.

PY - 1988/12

Y1 - 1988/12

N2 - The authors establish the notion of strong stochastic convexity (SSCX), which implies stochastic convexity. They demonstrate that SSCX is a property exhibited by a wide range of random variables. They also show that SSCX is preserved under random mixture, random summation, and any increasing and convex operations that are applied to a set of independent random variables. Making use of the closure property of SSCX, the authors study GI/G/1 queues and tandem queues with general interarrival and service times and finite intermediate buffers. Applications of the SSCX property in the parametric optimization of such systems are also discussed.

AB - The authors establish the notion of strong stochastic convexity (SSCX), which implies stochastic convexity. They demonstrate that SSCX is a property exhibited by a wide range of random variables. They also show that SSCX is preserved under random mixture, random summation, and any increasing and convex operations that are applied to a set of independent random variables. Making use of the closure property of SSCX, the authors study GI/G/1 queues and tandem queues with general interarrival and service times and finite intermediate buffers. Applications of the SSCX property in the parametric optimization of such systems are also discussed.

UR - https://www.scopus.com/pages/publications/0024172532

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0024172532&origin=recordpage

U2 - 10.1109/CDC.1988.194392

DO - 10.1109/CDC.1988.194392

M3 - RGC 22 - Publication in policy or professional journal

SN - 0191-2216

SP - 657

EP - 662

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

T2 - Proceedings of the 27th IEEE Conference on Decision and Control

Y2 - 7 December 1988 through 9 December 1988

ER -

Strong stochastic convexity and its applications in parametric optimization of queueing systems

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