Performance Modeling of Client-Server with Wibree Application Using Queueing Petri Nets and Markov Algorithm

V. Kirubanand, S. Palaniammal
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引用次数: 1

Abstract

This paper focuses on  how the petri net models can be exploited by markov algorithm for performance modelling of client server using Wibree applications. We study a real world application and demonstrate the benefits in terms of modeling power and expressiveness that Wibree technology and QPN models with markov algorithm provide over conventional modeling paradigms such as queueing networks and petri nets. QPNs facilitate the integration of both hardware and software aspects of the system behavior in the improved model. This lends itself very well to modeling distributed component-based systems, such as modern e-business applications. Currently available tools and techniques for QPN analysis suffer the state space explosion problem, imposing a limit on the size of the models that are tractable. In addition to Wibree technology in the systems and using QPNs one can easily model simultaneous resource possession .synchronization, blocking and contentions for software resources. QPNs are very powerful as a performance analysis and prediction tool .Improved solution methods, which enables larger models to be analyzed and they need to be developed. By demonstrating the power of QPNs as a modeling paradigm in realistic scenarios. We hope to motivate further research in this area.
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基于排队Petri网和马尔可夫算法的客户端-服务器连接应用程序性能建模
本文重点研究了如何利用petri网模型和马尔科夫算法对使用Wibree应用程序的客户端服务器进行性能建模。我们研究了一个现实世界的应用程序,并展示了Wibree技术和带有马尔可夫算法的QPN模型在建模能力和表达能力方面的优势,这些优势优于排队网络和petri网等传统建模范例。qpn促进了改进模型中系统行为的硬件和软件方面的集成。这使得它非常适合建模基于分布式组件的系统,例如现代电子商务应用程序。目前可用的QPN分析工具和技术存在状态空间爆炸问题,这限制了可处理模型的大小。除了系统中的Wibree技术和使用qpn之外,还可以很容易地对软件资源的同时占有、同步、阻塞和争用进行建模。qpn作为一种性能分析和预测工具是非常强大的。改进了求解方法,使更大的模型能够被分析,它们需要被开发。通过在现实场景中展示qpn作为建模范式的力量。我们希望能推动这一领域的进一步研究。
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