cyclic queues
Recently Published Documents


TOTAL DOCUMENTS

27
(FIVE YEARS 0)

H-INDEX

9
(FIVE YEARS 0)

Author(s):  
Donald Gross ◽  
John F. Shortie ◽  
James M. Thompson ◽  
Carl M. Harris
Keyword(s):  

Author(s):  
Sanne R. Smits ◽  
Ivo Adan ◽  
Ton G. de Kok
Keyword(s):  

1992 ◽  
Vol 11 (4) ◽  
pp. 233-241 ◽  
Author(s):  
Xiao-Gao Liu ◽  
John A Buzacott
Keyword(s):  

1991 ◽  
Vol 28 (01) ◽  
pp. 131-145 ◽  
Author(s):  
J. George Shanthikumar ◽  
David D. Yao

A family of random variables {X(θ)} parameterized by the parameter θ satisfies stochastic convexity (SCX) if and only if for any increasing and convex function f(x), Ef[X(θ)] is convex in θ . This definition, however, has a major drawback for the lack of certain important closure properties. In this paper we establish the notion of strong stochastic convexity (SSCX), which implies SCX. We demonstrate that SSCX is a property enjoyed by a wide range of random variables. We 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. These closure properties greatly facilitate the study of parametric convexity of many stochastic systems. Applications to GI/G/1 queues, tandem and cyclic queues, and tree-like networks are discussed. We also demonstrate the application of SSCX in bounding the performance of certain systems.


1991 ◽  
Vol 28 (1) ◽  
pp. 131-145 ◽  
Author(s):  
J. George Shanthikumar ◽  
David D. Yao

A family of random variables {X(θ)} parameterized by the parameter θ satisfies stochastic convexity (SCX) if and only if for any increasing and convex function f(x), Ef[X(θ)] is convex in θ. This definition, however, has a major drawback for the lack of certain important closure properties. In this paper we establish the notion of strong stochastic convexity (SSCX), which implies SCX. We demonstrate that SSCX is a property enjoyed by a wide range of random variables. We 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. These closure properties greatly facilitate the study of parametric convexity of many stochastic systems. Applications to GI/G/1 queues, tandem and cyclic queues, and tree-like networks are discussed. We also demonstrate the application of SSCX in bounding the performance of certain systems.


1988 ◽  
Vol 26 (3) ◽  
pp. 241-267 ◽  
Author(s):  
Demetres D. Kouvatsos ◽  
John Almond

Sign in / Sign up

Export Citation Format

Share Document