scholarly journals On the nonoptimality of the foreground-background discipline for IMRL service times

2006 ◽  
Vol 43 (02) ◽  
pp. 523-534
Author(s):  
S. Aalto ◽  
U. Ayesta
Keyword(s):  
Hazard Rate ◽  
Residual Lifetime ◽  
Processor Sharing ◽  
Counter Example ◽  
Mean Delay ◽  
Mean Residual Lifetime ◽  
Service Disciplines ◽  
The Mean ◽  
Service Times ◽  
The One

It is known that for decreasing hazard rate (DHR) service times the foreground-background discipline (FB) minimizes the mean delay in the M/G/1 queue among all work-conserving and nonanticipating service disciplines. It is believed that a similar result is valid for increasing mean residual lifetime (IMRL) service times. However, on the one hand, we point out a flaw in an earlier proof of the latter result and construct a counter-example that demonstrates that FB is not necessarily optimal within class IMRL. On the other hand, we prove that the mean delay for FB is smaller than that of the processor-sharing discipline within class IMRL, giving a weaker version of an earlier hypothesis.

scholarly journals On the nonoptimality of the foreground-background discipline for IMRL service times

2006 ◽  
Vol 43 (2) ◽  
pp. 523-534 ◽  
Author(s):  
S. Aalto ◽  
U. Ayesta
Keyword(s):  
Hazard Rate ◽  
Residual Lifetime ◽  
Processor Sharing ◽  
Counter Example ◽  
Mean Delay ◽  
Mean Residual Lifetime ◽  
Service Disciplines ◽  
The Mean ◽  
Service Times ◽  
The One

It is known that for decreasing hazard rate (DHR) service times the foreground-background discipline (FB) minimizes the mean delay in the M/G/1 queue among all work-conserving and nonanticipating service disciplines. It is believed that a similar result is valid for increasing mean residual lifetime (IMRL) service times. However, on the one hand, we point out a flaw in an earlier proof of the latter result and construct a counter-example that demonstrates that FB is not necessarily optimal within class IMRL. On the other hand, we prove that the mean delay for FB is smaller than that of the processor-sharing discipline within class IMRL, giving a weaker version of an earlier hypothesis.

scholarly journals A Dynamic Failure Time Degradation-Based Model

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1532
Author(s):  
Abdulhakim A. Albabtain ◽  
Mansour Shrahili ◽  
Lolwa Alshagrawi ◽  
Mohamed Kayid
Keyword(s):  
Hazard Rate ◽  
Failure Time ◽  
Degradation Process ◽  
Residual Lifetime ◽  
Time To Failure ◽  
Lifetime Distributions ◽  
Mean Residual Lifetime ◽  
Aging Properties ◽  
Degradation Models ◽  
Characterization Property

A novel methodology for modelling time to failure of systems under a degradation process is proposed. Considering the method degradation may have influenced the failure of the system under the setup of the model several implied lifetime distributions are outlined. Hazard rate and mean residual lifetime of the model are obtained and a numerical situation is delineated to calculate their amounts. The problem of modelling the amount of degradation at the failure time is also considered. Two monotonic aging properties of the model is secured and a characterization property of the symmetric degradation models is established.

Characterization of matrix probability distributions by mean residual lifetime

1986 ◽  
Vol 100 (3) ◽  
pp. 583-589
Author(s):  
P. E. Jupp
Keyword(s):  
Symmetric Matrix ◽  
Probability Distributions ◽  
Random Variable ◽  
Residual Lifetime ◽  
Regularity Conditions ◽  
Mean Residual Lifetime ◽  
The Mean ◽  
Image Position ◽  
Vector Valued

The mean residual lifetime of a real-valued random variable X is the function e defined byOne of the more important properties of the mean residual lifetime function is that it determines the distribution of X. See, for example, Swartz [10]. References to related characterizations are given by Galambos and Kotz [3], pages 30–35. It was established by Jupp and Mardia[6] that this property holds also for vector-valued X. As (1·1) makes sense if X is a random symmetric matrix, it is natural to ask whether the property holds in this case also. The purpose of this note is to show that, under certain regularity conditions, the distributions of such matrices are indeed determined by their mean residual lifetimes.

Expected delay analysis of polling systems in heavy traffic

1998 ◽  
Vol 30 (02) ◽  
pp. 586-602 ◽  
Author(s):  
R. D. van der Mei ◽  
H. Levy
Keyword(s):  
Heavy Traffic ◽  
Waiting Times ◽  
Delay Analysis ◽  
Polling Systems ◽  
Heavy Load ◽  
Polling Model ◽  
Mean Delay ◽  
Service Disciplines ◽  
The Mean ◽  
Cyclic Polling

We study the expected delay in a cyclic polling model with mixtures of exhaustive and gated service in heavy traffic. We obtain closed-form expressions for the mean delay under standard heavy-traffic scalings, providing new insights into the behaviour of polling systems in heavy traffic. The results lead to excellent approximations of the expected waiting times in practical heavy-load scenarios and moreover, lead to new results for optimizing the system performance with respect to the service disciplines.

Expected delay analysis of polling systems in heavy traffic

1998 ◽  
Vol 30 (2) ◽  
pp. 586-602 ◽  
Author(s):  
R. D. van der Mei ◽  
H. Levy
Keyword(s):  
Heavy Traffic ◽  
Waiting Times ◽  
Delay Analysis ◽  
Polling Systems ◽  
Heavy Load ◽  
Polling Model ◽  
Mean Delay ◽  
Service Disciplines ◽  
The Mean ◽  
Cyclic Polling

We study the expected delay in a cyclic polling model with mixtures of exhaustive and gated service in heavy traffic. We obtain closed-form expressions for the mean delay under standard heavy-traffic scalings, providing new insights into the behaviour of polling systems in heavy traffic. The results lead to excellent approximations of the expected waiting times in practical heavy-load scenarios and moreover, lead to new results for optimizing the system performance with respect to the service disciplines.

scholarly journals Mean Residual Lifetimes of Consecutive-k-out-of-n Systems

2007 ◽  
Vol 44 (1) ◽  
pp. 82-98 ◽  
Author(s):  
Jorge Navarro ◽  
Serkan Eryilmaz
Keyword(s):  
Likelihood Ratio ◽  
Asymptotic Properties ◽  
Parallel Systems ◽  
Residual Lifetime ◽  
Series System ◽  
Likelihood Ratio Order ◽  
Mean Residual Lifetime ◽  
The Mean ◽  
Residual Lifetimes ◽  
Independent And Identically Distributed

In this paper we study reliability properties of consecutive-k-out-of-n systems with exchangeable components. For 2k ≦ n, we show that the reliability functions of these systems can be written as negative mixtures (i.e. mixtures with some negative weights) of two series (or parallel) systems. Some monotonicity and asymptotic properties for the mean residual lifetime function are obtained and some ordering properties between these systems are established. We prove that, under some assumptions, the mean residual lifetime function of the consecutive-k-out-of-n: G system (i.e. a system that functions if and only if at least k consecutive components function) is asymptotically equivalent to that of a series system with k components. When the components are independent and identically distributed, we show that consecutive-k-out-of-n systems are ordered in the likelihood ratio order and, hence, in the mean residual lifetime order, for 2k ≦ n. However, we show that this is not necessarily true when the components are dependent.

Sign in / Sign up

Export Citation Format

Share Document