• 대한산업공학회지
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• 제40권2호
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• pp.163-171
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• 2014

Epidemic models are used to analyze the spreading of epidemic diseases, estimate public health needs, and assess the effectiveness of mitigation strategies. Modeling scope of an epidemic model ranges from the regional scale to national and global scale. Most of the epidemic models developed in Korea are at the national scale using the equation-based model. While these models are useful for designing and evaluating national public health policies, they do not provide sufficient details. As an alternative, individual-based models at the regional scale are often used to describe disease spreading, so that various mitigation strategies can be designed and tested. This paper presents an individual-based epidemic spreading model at regional scale. This model incorporates 2005 census data to build the synthetic population in the model representing Daejeon in 2005. The model's capability is demonstrated by an example where we assess the effectiveness of several mitigation strategies using the model.

• 대한수학회논문집
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• 제26권2호
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• pp.321-338
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• 2011

In this paper, a class of delayed epidemic model with diffusion is investigated. By analyzing the associated characteristic transcendental equation, its linear stability is investigated and Hopf bifurcation is demonstrated. Some explicit formulae determining the stability and the direction of the Hopf bifurcation periodic solutions bifurcating from Hopf bifurcations are obtained by using the normal form theory and center manifold theory. Some numerical simulation are also carried out to support our analytical findings. Finally, biological explanations and main conclusions are given.

• Journal of Communications and Networks
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• 제16권6호
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• pp.656-666
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• 2014

In delay tolerant networks (DTNs), delay is inevitable; thus, making better use of buffer space to maximize the packet delivery rate is more important than delay reduction. In DTNs, epidemic routing is a well-known routing protocol. However, epidemic routing is very sensitive to buffer size. Once the buffer size in nodes is insufficient, the performance of epidemic routing will be drastically reduced. In this paper, we propose a buffer scheme to optimize the performance of epidemic routing on the basis of the Lagrangian and dual problem models. By using the proposed optimal buffer scheme, the packet delivery rate in epidemic routing is considerably improved. Our simulation results show that epidemic routing with the proposed optimal buffer scheme outperforms the original epidemic routing in terms of packet delivery rate and average end-to-end delay. It is worth noting that the improved epidemic routing needs much less buffer size compared to that of the original epidemic routing for ensuring the same packet delivery rate. In particular, even though the buffer size is very small (e.g., 50), the packet delivery rate in epidemic routing with the proposed optimal buffer scheme is still 95.8%, which can satisfy general communication demand.

• 한국시스템다이내믹스연구
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• 제14권4호
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• pp.37-62
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• 2013

The purpose of this paper is to find out some clues about effectiveness and implementing timing of the control measures against Foot-and-Mouth Disease (FMD) in Korea. To do that, the case of FMD, which broke out during November 2010 in Korea, is examined and constructed as a system dynamics simulation model. The implications of simulation result are as follows. First of all, it is most effective measure to prevent the movement of vehicle from infected farmhouse to other noninfected farmhouses, which are located far away, in the early stage of FMD diffusion. Secondly, earlier vaccination can be adopted as a reliable means to control the epidemic when FMD spreads widely. Finally, reducing the time to vaccinate the whole noninfected livestock is a little help to restrain the additional infections of FMD.

• Journal of Computing Science and Engineering
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• 제2권3호
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• pp.249-273
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• 2008

Epidemic protocols have two fundamental assumptions. One is the availability of a mechanism that provides each node with a set of log(N) (fanout) nodes to gossip with at each cycle. The other is that the network size N is known to all member nodes. While it may be trivial to support these assumptions in small systems, it is a challenge to realize them in large open dynamic systems, such as peer-to-peer (P2P) systems. Technically, since the most fundamental parameter of epidemic protocols is log(N), without knowing the system size, the protocols will be limited. Further, since the network churn, frequently observed in P2P systems, causes rapid membership changes, providing a different set of log(N) at each cycle is a difficult problem. In order to support the assumptions, the fanout nodes should be selected randomly and uniformly from the entire membership. This paper investigates one possible solution which addresses both problems; providing at each cycle a different set of log(N) nodes selected randomly and uniformly from the entire network under churn, and estimating the dynamic network size in the number of nodes. This solution improves the previously developed distributed algorithm called Shuffle to deal with churn, and utilizes the Shuffle infrastructure to estimate the dynamic network size. The effectiveness of the proposed solution is evaluated by simulation. According to the simulation results, the proposed algorithms successfully handle network churn in providing random log(N0 fanout nodes, and practically and accurately estimate the network size. Overall, this work provides insights in designing epidemic protocols for large scale open dynamic systems, where the protocols behave autonomically.

• 디지털융복합연구
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• 제16권7호
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• pp.259-265
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• 2018

수학모형의 한 유형인 구획모형은 전염병의 확산처럼 순차적인 이벤트나 프로세스로 구성된 동적 시스템의 변화를 분석하는 데 폭넓게 활용되어 왔다. 구획모형은 상자와 화살표로 표현되는 구획과 구획 간 관계로 구성된다. 이러한 원리는 stock과 flow로 구성되는 시스템다이내믹스(SD)의 모델링 원리와 비슷하다. 두 모형 모두 미분방정식을 이용하여 구조화된다. 이와 같은 두 모형 간 변환 가능성을 이용하여 국내 MERS 전염의 특징을 분석한 최근 연구의 SEIR 참조모형을 SD 관점에서 해석 변환한다. 변환된 SEIR 모형(Model 2)은 참조모형(Model 1)의 재현 결과와 비교하여 동일한 시뮬레이션 결과를 나타내었다. 본 연구는 전염병 구획모형의 구축에 도식과 미분방정식을 이용한 SD 방법론의 활용에 대한 인사이트를 제공하며, 변환된 SD 모형은 다른 전염병을 위한 참조모형으로 활용 가능하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2020-2037
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• 2017

In order to improve the energy efficiency of n-Epidemic routing protocol in opportunistic networks, in which a stable end-to-end forwarding path usually does not exist, a novel adjustment strategy for parameter n is proposed using learning atuomata principle. First, nodes dynamically update the average energy level of current environment while moving around. Second, nodes with lower energy level relative to their neighbors take larger n avoiding energy consumption during message replications and vice versa. Third, nodes will only replicate messages to their neighbors when the number of neighbors reaches or exceeds the threshold n. Thus the number of message transmissions is reduced and energy is conserved accordingly. The simulation results show that, n-Epidemic routing protocol with the proposed adjustment method can efficiently reduce and balance energy consumption. Furthermore, the key metric of delivery ratio is improved compared with the original n-Epidemic routing protocol. Obviously the proposed scheme prolongs the network life time because of the equilibrium of energy consumption among nodes.

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 2005년도 제57차 추계 학술대회 연제집
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• pp.489-489
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• 2005

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제31권2호
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• pp.131-158
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• 2024

This study investigates the impact of precautionary measures, such as isolating exposed individuals, wearing masks, and maintaining physical distance, on preventing infectious disease. A deterministic SEIQHRV epidemic model is employed for this purpose. The model's positivity, boundedness, disease-free, and endemic equilibrium points are identified. A sensitivity test assesses the impact of preventive measures on infected classes. Results show that a basic reproduction number less than unity drives disease eradiction, while a higher unity value encourages the adoption of preventive measures.

• 한국시뮬레이션학회논문지
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• 제27권3호
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• pp.65-73
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• 2018

본 논문에서는 시뮬레이션 분석 과정의 복잡성을 줄이고 시뮬레이션 다량 수행을 가능토록 하기 위해 Elastic Stack 기술을 이용한 시뮬레이션 결과 분석 환경을 제안한다. 제안된 Elastic Stack 기반 시뮬레이션 결과 분석 환경은 물리적으로 떨어진 다양한 자원 상에서 수행되고 있는 시뮬레이션의 결과들을 중앙의 분석 서버로 자동 전송하고, 전송된 데이터들을 일괄적으로 관리하여 일련의 처리 및 분석 작업이 쉽게 적용될 수 있도록 지원하며, 다양한 가시화를 제공하는 서비스를 연결하여 분석 결과를 게시하는 과정을 손쉽게 구성할 수 있도록 지원한다. 또한, 각 서비스를 네트워크를 이용한 느슨한 연결 상태로 수행할 수 있어 확장성(scalability)을 제공한다. 제안된 시뮬레이션 결과 분석 환경의 유용성을 확인하기 위해 전염병 확산 시뮬레이션을 수행하고 별도의 분리된 서버에서 이에 대한 일련의 분석이 진행되는 과정을 보인다.