Performance modelling of nonhomogeneous unreliable multiserver systems using MOSEL

Zreikat, Aymen I.; Bolch, Gunter; Sztrik, János

doi:10.1016/s0898-1221(03)90032-0

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…It has been an extensive use of the old version MOSEL (Al-Begain et al 2001) and the modified version of MOSEL with new constructs, MOSEL-2 (Wuechner 2003) ,in the literature in various applications. The old version of MOSEL has been used intensively for many years and most of these applications are in queueing networks, some of them are in (Zreikat and Bolch 2007;Al-Begain et al 2003;Zreikat et al 2003;Wüchner et al 2007;Gunter et al 2006;Wüchner et al 2005). However, MOSEL-2 language is also used in different applications to model 2G and 3G of mobile networks, some of these examples are in (Zreikat et al 2008;Wüchner et al 2004;Barner and Bolch 2003).…”

Section: Application Of Mosel-2 In the Literaturementioning

confidence: 99%

Application Of MOSEL-2 Language In Performance And Modeling Of Cellular Wireless Networks

Zreikat¹

2012

Shaping Reality Through Simulation - Edited By: Klaus G. Troitzsch, Michael Möhring, Ulf Lotzmann

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Today's cellular wireless networks must meet increasing challenges of handling a larger demand for service without a loss of quality, by maximizing the spectral efficiency of the network. Therefore, performance evaluation and modeling of cellular wireless networks is considered to be an important issue to overcome the problem of limited resources of the network. MOSEL-2 (MOdelling Specification and Evaluation Language) offers the ability to evaluate complex systems in a straight, simple and very friendly environment. The old version of MOSEL offers only performance evaluation of complex systems with exponential distribution. However, by the new version of MOSEL (i.e. MOSEL2) with new constructs, it is possible to handle other behaviors with non-exponential distribution. In this paper, the application of MOSEL-2 in cellular wireless networks with mix service is presented. The main objective of the call admission control algorithm and the analysis is to obtain lower handover blocking probability over the new call blocking probability for both voice and data connections, which leads to minimum grade-of-service (i.e. < 0.01) over the whole cell. The numerical analysis of the suggested model with the associated interesting performance measures proves the effectiveness of this simulation in describing and solving this type of systems.

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Section: Application Of Mosel-2 In the Literaturementioning

confidence: 99%

Application Of MOSEL-2 Language In Performance And Modeling Of Cellular Wireless Networks

Zreikat¹

2012

Shaping Reality Through Simulation - Edited By: Klaus G. Troitzsch, Michael Möhring, Ulf Lotzmann

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“…However, most cloud computing systems do in fact have heterogeneous servers (see, for example, [4], [30] and [14]). Furthermore, the Fastest Server First is a common policy implemented in such systems (see [30]). In this paper we present a framework that allows for the analysis of constrained capacity allocation in large scale heterogeneous server systems.…”

Section: Introductionmentioning

confidence: 99%

“…The afformentioned papers, and many others that use stochastic queueing models for cloud computing, assume homogeneous servers. However, most cloud computing systems do in fact have heterogeneous servers (see, for example, [4], [30] and [14]). Furthermore, the Fastest Server First is a common policy implemented in such systems (see [30]).…”

Section: Introductionmentioning

confidence: 99%

Delay-Minimizing Capacity Allocation in an Infinite Server-Queueing System

Hassin

Ravner

2019

Stochastic Systems

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We consider a service system with an infinite number of exponential servers sharing a finite service capacity. The servers are ordered according to their speed, and arriving customers join the fastest idle server. A capacity allocation is an infinite sequence of service rates. We study the probabilistic properties of this system by considering overflows from sub-systems with a finite number of servers. Several stability measures are suggested and analysed. The tail of the series of service rates that minimizes the average expected delay (service time) is shown to be approximately geometrically decreasing. We use this property in order to approximate the optimal allocation of service rates by constructing an appropriate dynamic program. * To appear in Stochastic Systems. † lravner@post.tau.ac.il

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