• Title/Summary/Keyword: 추계적 페트리네트

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A Call Admission Control Technique of Wireless Networks using Stochastic Petri Nets (추계적 페트리 네트를 이용한 무선망에서의 호 수락 제어 기법)

  • 노철우
    • 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.

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Power Management SRN Modeling based on Adaptive Timeout (적응적 타임아웃 기반 전력관리 SRN 모델링)

  • Ro, Cheul-Woo;Kim, Kyung-Min
    • 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.

Petri Nets Modelling and Performance Analysis of Multimedia Mobile Communication Systems for Channel Allocations (멀티미디어 이동 통신 시스템의 채널 할당을 위한 페트리 네트 모델링과 성능분석)

  • 노철우;최재승
    • 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.

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Error Handling SPN Modeling (에러처리 SPN 모델링)

  • Ro, Cheul Woo
    • 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.

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Availability Analysis of 2N Redundancy System Using Stochastic Models (안정적인 서비스를 위한 2N 이중화 모델의 가용도 분석)

  • Kim, Dong Hyun;Lee, Yutae
    • 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.

Channel Optimization in CDMA Systems (CDMA 시스템의 채널 최적화)

  • Ro Cheul-Woo;Lee Kwang-Eui;Kim Kyung-Min
    • The Journal of the Korea Contents Association
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    • v.6 no.9
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    • pp.1-8
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    • 2006
  • In a CDMA system, minimizing handoff calls is an important factor for user satisfaction. In this paper, we divide the cell area into two regions: normal region and soft handoff region. And we show that differentiating the guard channel numbers in those two regions make handoff calls minimized. We develop an SRN based cell model consists of normal and soft handoff region and analyze the performance of the model.

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Dynamic Power Management based on Stochastic Processes (추계적 프로세스 기반 동적 전력 관리)

  • Ro, Cheul Woo;Kim, Kyung Min;Paul, Muthusi
    • 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.

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Reliability Analysis Modeling of Communication Networks Considering Rerouting (재경로 설정을 고려한 통신망의 신뢰도 분석 모델링)

  • Ro, Cheul-Woo
    • 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.

Modeling of Virtual Switch in Cloud System (클라우드 시스템의 가상 스위치 모델링)

  • Ro, Cheul-Woo
    • 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.

SRN Hierarchical Modeling for Packet Retransmission and Channel Allocation in Wireless Networks (무선망에서 패킷 재전송과 채널할당 성능분석을 위한 SRN 계층 모델링)

  • 노철우
    • 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.

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