PETRI NET PERFORMANCE AND RELIABILITY MODELS FOR WIRELESS NETWORKS

Document Type : Original Article

Authors

1 National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt

2 Electrical Engineering Department., Faculty of Eng., Al-Azhar University, Cairo, Egypt

3 Systems & Computers Eng. Department, Faculty of Eng., Al-Azhar University, Cairo, Egypt

Abstract

Since the dynamic behavior of wireless networks inherits different communication patterns
for the execution processes of the desired parallel tasks and the occurrence processes of handoff
operations, the available reliability metrics are not applicable to study and analyze such networks.
Therefore, in this paper, we propose a novel Petri net modeling methodology for accurately calculating
the reliability of wireless networks that incorporate theses aspects, such as wireless CORBA network.
The proposed reliability methodology is developed based on using the End-to-End Expected
Instantaneous Reliability (EIR) measure. The EIR has the capability to measure the reliability of
wireless networks that incorporate the handoff processes as well as the service processes. In the
proposed technique, we firstly build Generalized Stochastic Petri Net (GSPN) performance model for
describing the different communication pattern that can occur among the various network resources
under the execution of parallel tasks. Secondly, we build GSPN performance model for describing the
handoff communication processes among the various network resources. Finally, we build generic
reliability model consists of the following parts: the first part describes the execution of the desired
parallel tasks, the second part illustrates the mobility characteristic introduced by handoff processes,
and the third part describes the dynamic behavior of failure processes of network resources. We study
and analyze the various reliability results as well as the performance results obtained from the
developed GSPN models under the effect of communication distance among the CORBA network
resources.
International Journal of Intelligent Computing and Information Sciences
Volume 14, Issue 1
January 2014
Pages 81-107

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