• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.55-62
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• 2003

In this paper, a call admission contro(cac) technique is proposed to reduce the dropping probabilities of handoff calls in wireless networks while guaranteeing QoS to the users. The proposed technique is based on the estimated effective load for the target eel if a call is accepted. When the estimated effective load is higher than a predetermined threshold, a nu call is blocked and a handoff call is queued irrespective of the availability channels. The SRN, an extended Stochastic Petri Net, modes are constructed to compare the performance of the techniques. The SRN uses rewards concepts instead of the complicate numerical analysis required for the Markov chain modes. As a result, the SRN modeling techniques provide an easier way to carry out performance analysis for call admission control and channel allocation.

• 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.

• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.704-711
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• 2002

Multimedia communication systems are characterized by supporting three different typer of services such as circuit switched services, and packet switched real Lime and non real time services. The wireless channels in a cell ate allocated by calls of these different service classes and the different service requirements have to be met. SRN is an extension of stochastic Petri nets and provides compact Modeling facilities for system analysis. To get the performance index, appropriate reward rates are assigned to its SRN. In this paper, we present a SRN model for performance analysis of channel allocation of multimedia mobile communication systems. 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 allocations under SRN rewards concepts.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.569-570
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• 2011

fault와 에러를 구분하여 정의한 후, 에러처리를 위한 시스템 상태를 fault, 에러, 회복, benign, mon1, mon2의 상세 상태로 분류하고, 이들 상태를 묘사해 줄 수 있는 추계적 페트리 네트를 이용하여 시스템 에러 처리를 모델링 한다. 시스템이 수십년이 지나면 궁극적으로 다운되는 비신뢰도를 모델로 부터 구할 수 있음을 보여준다.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.45-52
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• 2009

In this paper, we develop queueing network models of communication networks with reliability model considering link failures. The reliability of a communication network with a virtual connection exposed to link failures is analyzed. Stochastic Reward Nets (SRN) is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. To get the performance index, appropriate reward rates are assigned to its SRN. It is shown that SRN modeling is well suited to specify, automatically generate and solve for reliability under rerouting. Markov models using SRN are developed and solved to depict various rerouting caused by link failures and reliability analysis in communication networks.

• 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.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.479-485
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• 2013

Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance isolated platforms called virtual machines. Through server virtualization software, applications servers are encapsulated into VMs, and deployed with APIs on top generalized pools of CPU and memory resources. Networking and security have been moved to a software abstraction layer that transformed computing, network virtualization. And it paves the way for enterprise to rapidly deploy networking and security for any application by creating the virtual network. Stochastic reward net (SRN) is an extension of stochastic Petri nets which provides compact modeling facilities for system analysis. In this paper, we develop SRN model of network virtualization based on virtual switch. Measures of interest such as switching delay and throughput are considered. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results are obtained according to the virtual switch capacity and number of active VMs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2634-2639
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• 2014

The idea of redundancy is used in order to improve the availability of networks and systems and there are various methods for implementing redundancy. To perform the availability analysis various stochastic models have been used. In this paper, 2N redundancy with one active service unit and one standby service unit is considered. To evaluate the expected availability, we model 2N redundancy using Stochastic Reward Nets. This model can be solved using the SPNP package.

• IE interfaces
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• v.8 no.2
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• pp.161-169
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• 1995

In this paper, a threshold policy is considered for the Markovian queueing system with server vacations. The threshold policy considered in this paper has the following form: "when the number of customers present in the system increases to N, the server is turned on and serves customers until the system becomes empty". In this paper, we show how the finite capacity or finite population queueing system under a threshold policy can be modeled by the stochastic Petri net. The performance evaluation of the model is carried out using the software called "SPNP". Some examples are also presented in which it is shown that how the optimal threshold policies can be obtained under a linear cost structure.

• The KIPS Transactions:PartC
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• v.8C no.1
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• pp.97-104
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• 2001

In this paper, we present a new hierarchical model for performance analysis of channel allocation and packet service protocol in wireless n network. The proposed hierarchical model consists of two parts : upper and lower layer models. The upper layer model is the structure state model representing the state of the channel allocation and call service. The lower layer model, which captures the performance of the system within a given structure state, is the wireless packet retransmission protocol model. These models are developed using SRN which is an modeling tool. SRN, an extension of stochastic Petri net, provides compact modeling facilities for system analysis. To get the performance index, appropriate reward rates are assigned to its SRN. Fixed point iteration is used to determine the model parameters that are not available directly as input. That is, the call service time of the upper model can be obtained by packet delay in the lower model, and the packet generation rates of the lower model come from call generation rates of the upper model.