• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.4
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• pp.1-14
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• 1995

A new stochastic Petri nets model, called Stochastic Petri Nets Reward Model(SPNRM) is used for modeling and evaluating the performance of telecommunication protocols. We have developed a SPNRM of the TDX-10 Internal protocol, which has a packet data exchange facility between DCEs, Especially a timer and retransmission handling model is presented for error control of the data transmission phase. The stochastic Petri nets package(SPNP), a software package for SPNRM used in this paper, has been used to generate numerical results by analytical-numerical method rather than simulation. From the steady state solution of the net, it is possible to calculate automatically the performance measure of the protocol medeled with both end-to-end and link-by-link method, which are the mean response times and the throughputs.

• International Journal of Contents
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• v.4 no.3
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• pp.20-28
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• 2008

To obtain realistic performance measures for wireless networks, one should consider changes in performance due to failure related behavior. In performability analysis, simultaneous consideration is given to both pure performance and performance with failure measures. SRN is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. In this paper, a new methodology to model and analyze performability based on stochastic reward nets (SRN) is presented. Composite performance and availability SRN models for wireless handoff schemes are developed and then these models are decomposed hierarchically. The SRN models can yield measures of interest such as blocking and dropping probabilities. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results show the accuracy of the hierarchical model. The key contribution of this paper constitutes the Petri nets modeling techniques instead of complicate numerical analysis of Markov chains and easy way of performance analysis for channel allocation under SRN reward concepts.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.300-307
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• 2008

Power management (PM) depends on the power state transition and system workload. The system model is composed of corresponding stochastic models of the power state and system queue. In this paper, stochastic models which can handle various PM techniques are developed. SRN (Stochastic Reward Nets), an extended Petri-Net, has facilities that represent system queue and various modelling functions. The SRN is employed for developing PM models. An adaptive timeout PM model is also introduced and the power consumption and performance of this model are compared with other existing PM techniques models such as greedy and N-Policy techniques.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.169-176
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• 2008

In this paper, we develop radio resource management queueing model in IEEE 802.IS networks considering both connection and packet level. In the upper level connection, we model connection admission control depending on availability of bandwidth and priority queue in each service class. In the lower level packet, we model dynamic bandwidth allocation considering threshold and availability of bandwidth in each service class simultaneously. Hierarchical model is built using an extended Petri Nets, SRN (Stochastic Reward Nets). Bandwidth utilization and normal throughput as performance index for all service classes of traffic are calculated and numerical results are obtained.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.390-392
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• 2010

Mobile grid system supports the integration mobile devices as grid resources. Availability of mobile resources changes dynamically in mobile grid system. Stochastic reward nets (SRN) is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. We build the SRN model to represent availability of mobile resources with disconnected operation service.

• International Journal of Contents
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• v.6 no.4
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• pp.30-34
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• 2010

Effective job scheduling scheme is a crucial part of complex heterogeneous distributed systems. Gang scheduling is a scheduling algorithm for grid systems that schedules related grid jobs to run simultaneously on servers in different local sites. In this paper, we address grid jobs (gangs) schedule modeling using Stochastic reward nets (SRNs), which is concerned for static and dynamic scheduling policies. SRN is an extension of Stochastic Petri Net (SPN) and provides compact modeling facilities for system analysis. Threshold queue is adopted to smooth the variations of performance measures. System throughput and response time are compared and analyzed by giving reward measures in SRNs.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.197-200
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• 2007

Dynamic power management reduces the power consumption of the system by switching system components into different power states, which have different power consumption levels. The main function of a power management is to decide when to perform state transitions. In this paper, a power management model based on stochastic processes is introduced. This model is developed using SRN (Stochastic Reward Nets), which has facilities to represent system queue and various modeling functions.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.699-705
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• 2009

This paper reviews methods used to perform reliability and availability analysis of the network system composed by nodes and links. The combination of nodes and links forms virtual connections (VC). The failure of several VCs cause failure of whole network system. Petri Net models are used to analyze the reliability and availability. Stochastic reward nets (SRN) is an extension of stochastic Petri nets provides modelling facilities for network system analysis.

• International Journal of Contents
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• v.6 no.3
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• pp.19-24
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• 2010

Task scheduling is an integrated component of computing with the emergence of grid computing. In this paper, we address two different task scheduling models, which are static Round-Robin (RR) and dynamic Fastest Site First (FSF) task scheduling method, using extended timed marked graphs, which is a special case of Stochastic Petri Nets (SPN). Stochastic reward nets (SRN) is an extension of SPN and provides compact modeling facilities for system analysis. We build hierarchical SRN models to compare two task scheduling methods. The upper level model simulates task scheduling and the lower level model implements task serving process for different sites with multiple servers. We compare these two models and analyze their performances by giving reward measures in SRN.

• International Journal of Contents
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• v.5 no.4
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• pp.88-93
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• 2009

It is important for communication networks to possess the capability to overcome failures and provide survivable services. We address modeling and analysis of performability affected by both performance and availability of system components for a token ring network under failure and repair conditions. Stochastic reward nets (SRN) is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. In this paper, hierarchical SRN modeling techniques are used to overcome state largeness problem. The upper level model is used to compute availability and the lower level model captures the performance. And Normalized Throughput Loss (NTL) is obtained for the composite ring network for each node failures occurrence as a performability measure. One of the key contributions of this paper constitutes the Petri nets modeling techniques instead of complicate numerical analysis of Markov chains and easy way of performability analysis for a token ring network under SRN reward concepts.