인하대학교 소프트웨어 공학
연구실에서는 신입 대학원생
과 예비 대학원생을 모집
합니다. 연구실 지원을
희망하는 학생은 하이테크관
1407호 로 방문 또는
아래의 연락처로
연락 주시기 바랍니다.
TEL: (032) 860-7454
Email: inhaselab@gmail.com
Software Engineering Laboratory.
Software Modeling and System
Researchers: Tae Young Kim (18th semester), Hyunchang Oh (12th semester)
Related Published List:
1. Taeyoung Kim, Youngshin Han, Jaekwon Kim, Jongsik Lee, "Adaptive Flow QoS Management Model for Wireless Communication in Mobile Environments", Acta Polytechnica Hungarica (indexed by SCIE), Volume 13 Issue Number 2, March 2016
2. Taeyoung Kim, Youngshin Han, Jaekwon Kim, Jongsik Lee, "Fuzzy Logic-based Adaptive Communication Management on Wireless Network", 6th International Conference on Computational Collective Intelligence (ICCCI 2014), LNAI 8733, Seoul, South Korea, September 2014
3. Tae Young Kim, Jong Sik Lee, "Multi-policy based Scheduling for Face Certification on Distributed Computing", Information: An International Interdisciplinary Journal (Printed in Japan) (indexed by SCOPUS), Volume 16, Number 12(A), December 2013
4. Taeyoung Kim, Jaekwon Kim, Minoh Park, Sanggil Kang, Kangsun Lee, Jong Sik Lee, "Agent-based Flexible Management for Big Data Fusion Service on IRC Network", The Second International Conference on Big Data Science and Engineering (BDSE2013), Sydney, Austrailia, December 2013
5. Tae-young Kim, Kang Sun Lee, Jong Sik Lee, "The Study of Modeling and Simulation Management and Tools for Distributed Real-time Simulation Engine", 2013 International Military Science and Technology Fair, Seoul, South Korea, July 2013
6. 이석우, 이종식, "자원 가용성 기반 다중 경매 모델을 이용한 클라우드 자원 거래 시스템의 물리자원 집합체 상태 관리 시스템", 한국시뮬레이션학회 2013년 춘계학술대회, 한국항공대학교, May 2013
7. 박민오, 이종식, "클라우드 컴퓨팅 환경에서 재이주 상황 발생 시 퍼지로직 기반 우선순위 재이주 방법", 한국시뮬레이션학회 2013년도 춘계학술대회, 한국항공대학교, May 2013
8. 김태영, 김재권, 오현창, 이석우, 박민오, 조동욱, 이종식, "자원 신뢰도 계층의 동적 관리를 이용한 클라우드 자원 할당 및 거래 시스템", 제23회 통신정보 합동학술대회, 경주 현대호텔, May 2013
9. 김태영, 김재권, 오현창, 이석우, 박민오, 조동욱, 이종식, "자원 신뢰도 계층의 동적 관리를 이용한 클라우드 자원 할당 및 거래 시스템", 제23회 통신정보 합동학술대회, 경주 현대호텔, May 2013
10. Yong Beom Ma, Tae Young Kim, Jae Kwon Kim, Jong Sik Lee, "Fuzzy Logic-based Battle Field Mobility Prediction Method in War-game Simulation", The 44th Summer Computer Simulation Conference (SCSC 2012), Architecture Complex, Genoa University, Genoa, Italy, July 2012
11. 김재권, 이종식, "그리드 컴퓨팅에서 유효자원 동적 재배치 기반 작업 스케줄링 모델", 한국시뮬레이션학회 논문지, 제21권 2호, June 2012
12. 김태영, 마용범, 김재권, 이종식, "다층 구조 모델을 이용한 분산 전장 이동 시뮬레이션 방안 연구", 한국시뮬레이션학회 2012년도 춘계학술대회, 연세대학교 원주캠퍼스, May 2012
13. 이석우, 김재권, 이종식, "스마트그리드에서 시계열과 퍼지를 이용한 장기 전력 수요 예측 및 전력 패턴 변화 분석", 한국시뮬레이션학회 2012년 춘계학술대회, 연세대학교 원주캠퍼스, May 2012
14. 이종식, 김태영, "그리드 생체정보 인증 시스템에서의 부하 분산 스케줄링을 위한 시뮬레이션 기반 작업부하 예측모델 선택 시스템 및 방법", 인하대학교 산학협력단 특허 등록번호 10-1142237, April 2012
15. 마용범, 김재권, 이종식, "워게임 시뮬레이션에서 온톨로지 기반의 경로탐색 모델링 및 시뮬레이션", 한국시뮬레이션학회 논문지, 제21권 1호, March 2012
16. Kyu Cheol Cho Jong Sik Lee, "Grid-based & Outlier Detection-based Data Clustering & Classification", INFORMATION: An International Journal, Vol.15, No.3, March 2012
17. 김재권, 이종식, "클라우드 환경의 교통정보 서비스를 위한 조건부 확률 추론을 이용한 가상 머신 프로비저닝 스케줄링", 한국시뮬레이션학회 논문지, 제20권 4호, December 2011
18. Tae Young Kim Jong Sik Lee, "Workload Prediction and Weighted Rule-Based Task Scheudling for Face Certificatoin System on Distributed Parallel Computing", Grid and Distributed Computing, CCIS 261, Jeju Island, Korea, December 2011
19. 이종식 마용범, "온톨로지 기반의 속도 추론을 이용한 이동성 예측 시스템 및 그 방법", 인하대학교 산학협력단 특허 등록번호 10-1092089, December 2011
20. Yong Beom Ma, Sung Ho Jang, Jong Sik Lee, "QoS and Ontology-based Resource Management in Cloud Computing Environment", INFORMATION: An International Journal, Vol.14, No.11, November 2011
21. Yong Beom Ma, Jong Sik Lee, "Intelligent Agent-based Mobility Prediction Method using Velocity Inference", Asia Simulation Conference (AsiaSim) 2011, Seoul, Korea, November 2011
22. Hyunchang Oh, Jong Sik Lee, "Battlefield Data Quantization Method for War-game Optimal Path Generation in Distributed Simulation", Asia Simulation Conference (AsiaSim) 2011, Seoul, Korea, November 2011
23. 송승현 이종식 장성호, "가용율 기반의 서버 재설정 장치 및 방법", 인하대학교 산학협력단 특허 등록번호 10-1081286, November 2011
24. 노창현 김태영 이종식, "분산 처리를 위한 시멘틱 컴퓨팅 기반의 동적 작업 스케줄링 시스템", 인하대학교 산학협력단, 특허 등록번호 10-1055548, August 2011
25. 오현창 이종식, "분산시뮬레이션을 이용한 워게임 이동객체의 최적경로 생성 시스템", 한국시뮬레이션학회 2011 춘계학술대회, 경기대학교 수원캠퍼스, May 2011
26. 김재권 이종식, "스마트 그리드 환경 기반의 홈 네트워크의 수요반응을 이용한 전력부하 예측모델", 한국시뮬레이션학회 2011 춘계학술대회, 경기대학교 수원캠퍼스, May 2011
27. Yong Beom Ma, Sung Ho Jang, Jong Sik Lee, "Ontology-based Resource Management for Cloud Computing", The 3rd Asian Conference on Intelligent Information and Database Systems (ACIIDS) 2011, Daegu, Korea, April 2011
28. 이종식 김태영, "분산처리 기반 인체인식을 위한 퍼지추론 기반 비트 압축 시스템", 인하대학교 산학협력단, 특허 등록번호 10-1029417, April 2011
29. 장원석 이종식, "퍼지 및 부스팅 기법을 통한 얼굴 특징 선택 방법 및 장치", 인하대학교 산학협력단 특허 등록번호 10-1014506, February 2011
30. Sung Ho Jang Jong Sik Lee, "Mobile Resource Reliability-based Job Scheduling for Mobile Grid", KSII Transactions on Internet and Information Systems, Vol.5, Issue 1, January 2011
31. 장원석 이종식, "부스팅 기법을 통한 얼굴 인식 방법 및 장치", 인하대학교 산학협력단, 특허 등록번호 10-0998842, November 2010
32. 조수현 이종식, "효과적인 교통 흐름 제어를 위한 휴대용 무선 단말기를 이용한 분산 시뮬레이션", 한국시뮬레이션학회 2010 추계학술대회, 명지대학교 용인캠퍼스, October 2010
33. Sung Ho Jang Jong Sik Lee Chang Hyeon Noh Young Shin Han, "Ontology-based Adaptive Job Scheduling Using Mobile Agent Technology in Grid Computing", INFORMATION: An International Journal, Vol.13, No.5, September 2010
34. 이성용 장성호 이종식, "워게임 시뮬레이션에서 전장상황을 고려한 최적경로 모델링 및 시뮬레이션", 한국시뮬레이션학회, 제19권3호, September 2010
35. Kyu Cheol Cho Sung Ho Jang Chang Hyeon Noh Tae Young Kim Jong Sik Lee Jae Min Lee Tae Sup Kim Kang Sun Lee, "Route Reasoning-based Mobility Modeling and Simulation for Street Fight using DEVS", Summer Computer Simulation Conference 2010, Ottawa, Canada, July 2010
36. 마용범 김태영 이종식, "동적 로드 밸런싱을 이용한 그리드 기반의 생물학적 데이터 마이닝", 한국시뮬레이션학회 제19권 2호, June 2010
37. 이종식 조규철, "온톨로지 추론을 이용한 그리드 자원 관리장치", 인하대학교산학협력단 특허 등록번호 10-0967120, June 2010
38. 이성용 최학진 마용범 이종식, "시가전에서 전차 이동경로 알고리즘을 이용한 전투모의훈련 모델링 및 시뮬레이션", 한국시뮬레이션학회 2010 춘계학술대회, 홍익대학교 조치원캠퍼스, May 2010
39. 이성용 최학진 마용범 이종식, "시가전에서 전차 이동경로 알고리즘을 이용한 전투모의훈련 모델링 및 시뮬레이션", 한국시뮬레이션학회 춘계 학술대회, May 2010
40. 장성호 김태영 이종식, "분산 컴퓨팅 환경에서의 워게임 시뮬레이션을 위한 네트워크 트래픽 제어", 한국시뮬레이션학회 논문지 제18권 4호, December 2009
41. 조규철 장성호 김태영 이종식, "분산 컴퓨팅 환경에서 워 게임의 시가전 모델링과 시뮬레이션", 한국시뮬레이션학회 2009 추계학술대회, 이화여자대학교, October 2009
42. 이성용 장성호 이종식, "전장에서 소대이동시 유전자 알고리즘을 이용한 최적 경로 모델링 및 시뮬레이션", 한국시뮬레이션학회 2009 추계학술대회, 이화여자대학교, October 2009
43. Yong Beom Ma Tae Young Kim Seung Hyeon Song Jong Sik Lee, "Analysis and Experimentation of Grid-based Data Mining with Dynamic Load Balancing", International Conference on Advanced Data Mining and Applications (ADMA) 2009, Lecture Notes in Artificial Intelligence, 5678, Beijing, China, August 2009
44. 김태영 노창현 이종식, "분산 얼굴인식을 위한 퍼지로직 기반 비트 압축법", 한국 시뮬레이션학회 논문지 제 18권 2호, June 2009
45. 노창현 장성호 김태영 이종식, "시멘틱 컴퓨팅 기반의 동적 작업 스케줄링 모델 및 시뮬레이션", 한국 시뮬레이션학회 논문지 제 18권 2호, June 2009
46. Yong Beom Ma Chang Hyeon Noh Jong Sik Lee, "Ontology-based Resource Management Model for Computational Grid", International Conference on Convergence and hybrid Information Technology (ICCIT 2008), Busan, Korea, November 2008
47. Kyu Cheol Cho Tae Young Kim Jong Sik Lee, "User Demand Prediction-Bsed Resource Management Model in Grid Computing Environment", IEEE International Conference On Convergence & Hybrid Information Technology 2008, Daejeon, Korea, August 2008
48. 노창현 장성호 김태영 이종식, "온톨로지 기반의 그리드 자원선택 시스템", 한국컴퓨터정보학회 논문지 제 13권 3호, May 2008
49. 노창현 조규철 마용범 이종식, "의사결정 트리 기법을 이용한 그리드 자원선택 시스템", 한국컴퓨터정보학회 논문지 제 13권 1호, January 2008
50. Sung Ho Jang Jong Sik Lee, "Node Availability-based Congestion Control Model using Fuzzy Logic for Computational Grid", Future Generation Communication and Networking 2007(FGCN 2007),, Cheju Island, South Korea, December 2007
51. 박량재 장성호 조규철 이종식, "계산 그리드를 위한 퍼지로직 기반의 그리드 작업 스케줄링 모델", 한국컴퓨터정보학회논문지 제12권 제6호, November 2007
52. 마용범 이종식, "그리드 컴퓨팅 환경에서의 자원 관리를 위한 분산화된 브로커 기반 모델", 한국시뮬레이션학회 논문지, 제16권 2호, June 2007
53. 박다혜 이종식, "계산 그리드 컴퓨팅에서의 자원 성능 측정을 통한 그리드 스케줄링 모델", 한국컴퓨터정보학회 논문지, 제11권 5호, November 2006
54. 장성호 전나예 이종식, "계산 그리드의 효과적인 자원관리를 위한 자원 신뢰도 예측모델", 한국시뮬레이션학회 2006 추계 학술대회, November 2006
55. 박량재 장성호 이종식, "그리드 컴퓨팅을 위한 자원지연시간 기반 클러스터링 기법을 이용한 작업 스케줄링 모델", 한국시뮬레이션학회 2006 추계 학술대회, November 2006
56. In Kee Kim Yong Beom Ma Jong Sik Lee, "Adaptive Quantization-based Communication Data Management for High-Performance Geo-computation in Grid Computing", International Workshop on High Performance Geo-computation At the 5th International Conference on Grid and Cooperative Computing 2006, October 2006
57. 마용범 이종식, "사용자 요구 기반의 그리드 거래 관리 모델", 한국시뮬레이션학회 논문지, 제15권 3호, September 2006
58. 박다혜 이종식, "그리드 컴퓨팅에서 자원 신뢰성 측정 시뮬레이션 모델", 한국시뮬레이션학회 2006 춘계 학술대회, May 2006
59. 마용범 이종식, "그리드 컴퓨팅 환경에서의 로컬 브로커 기반 자원 관리 모델", 한국시뮬레이션학회 2006 춘계 학술대회, May 2006
60. Jong-Sik Lee Yong-Beom Ma Kyoung-Soo Choi Sun-Hee Baek Ke Zu Haitao Zhang Clement Ip Soo-Yeon Park Yeul Hong Kim Eun-Mi Park Young-Mee Park, "Neural network-based analysis of thiol proteomics data in identifying potential selenium targets", Special Proteomics Issue of Preparative Biochemistry and Biotechnology, in press 2005, December 2005
61. Sung Ho Jang Da Hye Park Jong Sik Lee, "Grid Resource Trade Network: Effective Resource Management Model in Grid Computing", LECTURE NOTES IN COMPUTER SCIENCE, 3795, November 2005
62. Jong Sik Lee , "Communication Data Multiplexing in Distributed Simulation", LECTURE NOTES IN COMPUTER SCIENCE, 3719, October 2005
63. Jong S. Lee , "High Performance Modeling for Distributed Simulation", LECTURE NOTES IN COMPUTER SCIENCE, 3397, February 2005
64. Jong S. Lee , "Scalable Data Management Modeling and Framework for Grid Computing", LECTURE NOTES IN COMPUTER SCIENCE, 3251, October 2004
65. Jong Sik Lee , "High Performance System Modeling and Performance Evaluation for Grid Computing", PDPTA 04 - The 2004 International Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, Nevada, June 2004
66. Jong S. Lee , "High Performance Modeling with Quantized System", LECTURE NOTES IN COMPUTER SCIENCE, 3045, May 2004
67. Jong Sik Lee , "Quantized System Modeling and Performance Evaluation", 한국시뮬레이션학회 추계학술대회, November 2003
68. Jong Sik Lee , "Discrete Event System Modeling and Evaluation", 제2회 한국소프트웨어 감정평가학회 추계학술대회, November 2003
69. Jong S. Lee B. P. Zeigler, "High Performance Modeling of Ballistic Missile Federations in DEVS/GDDM", Advanced Simulation Technologies Conference, Orlando, FL, April 2003
70. Jong S. Lee Bernard. P. Zeigler, "Space-based Communication Data Management in Scalable Distributed simulation", Journal of Parallel and Distributed Computing, 62, (doi:10.1006/jpdc.2001.1798), available online http://www.idealibrary.com, March 2003
71. Sung-Do Chi Syng-Yup Ohn Kyoung-Soo Choi Eung-Sik Kong Jong Sik Lee Chul Woo Kim Young-Mee Park, "Development of Classification Algorithms to Identify Breast Cancer", New York State Proteomics Symposium, Syracuse, NY, March 2003
72. Bernard P. Zeigler Hyup J. Cho Jeong G. Kim Hessam Sarjoughian Jong S. Lee, "Quantization based filtering in distributed simulation: experiments and analysis", Journal of Parallel and Distributed Computing, Volume 62, number 11, November 2002
73. J.S. Lee B. P. Zeigler, "Development of DEVS/GDDM Environment: Realization of Space-based Data Management", IEEE Systems, Man, and Cybernetics Conference, October 2001
74. Ernesto Kofman Jong S. Lee B. P. Zeigler, "DEVS Representation of Differential Equation Systems: Review of Recent Advances", European Simulation Symposium and Exhibition, DEVS Workshop, Marseilles, France., October 2001
75. Bernard. P. Zeigler Hessam Sarjoughian Sunwoo Park James Nutaro Jong S. Lee Y.K. Cho, "DEVS Modeling And Simulation: A new layer of Middleware", Advanced Middleware Systems proceedings of the IEEE high performance distributed systems, San Francisco, CA, August 2001
76. Jong Sik Lee Bernard. P. Zeigler, "Design and Development of Data distribution Management Environment", Journal of Society of Computer Simulation, Simulation, (77)1-2, July 2001
77. Bernard. P. Zeigler Hyup Cho J.S. Lee Y.K. Cho Hessam Sarjoughian, "Predictive Contract Methodology and Federation Performance", Simulation Interoperability Workshop (SIW) 99F-SIW-161, Orlando, FL., September 1999
78. Bernard. P. Zeigler George Ball Hyup Cho J.S. Lee, "Implementation of the DEVS Formalism over the HLA/RTI: Problems and Solutions", Simulation Interoperability Workshop (SIW), 99S-SIW-65, Orlando, FL, June 1999
79. Bernard. P. Zeigler George Ball Hyup Cho J.S. Lee Hessam Sarjoughian, "Bandwidth Utilization/Fidelity Tradeoffs in Predictive Filtering", Simulation Interoperability Workshop (SIW), 99S-SIW-63, Orlando, FL., June 1999
80. Zeigler B.P J.S. Lee, "Theory of Quantized Systems: Formal Basis for DEVS/HLA Distributed Simulation Environment", Enabling Technology for Simulation Science(II), SPIE AeoroSense 98, vol.3369, April 1998
Discrete Event System Modeling
Framework for Modeling and Simulation
The Discrete Event System Specification (DEVS) formalism provides a means of specifying a mathematical object called a system. Basically, a system has a time base, inputs, states, and outputs, and functions for determining next states and outputs given current states and inputs. Discrete event systems represent certain constellations of such parameters just as continuous systems do. For example, the inputs in discrete event systems occur at arbitrarily spaced moments, while those in continuous systems are piecewise continuous functions of time. The insight provided by the DEVS formalism is in the simple way that it characterizes how discrete event simulation languages specify discrete event system parameters. Having this abstraction, it is possible to design new simulation languages with sound semantics that easier to understand. Indeed, the DEVJAVA environment to be described later is an implementation of the DEVS formalism in Java which enables the modeler to specify models directly in its terms.
Brief Review of the DEVS Concepts
The modeling and simulation enterprise concerns three basic objects:
the real system, in existence or proposed, which is regarded as fundamentally a source of data model, which is a set of instructions for generating data
comparable to that observable in the real system. The structure of the model is its set of instructions. The behavior of the model is the set of all possible data that can be generated by faithfully executing the model instructions.
simulator, which exercises the model's instructions to actually generate its behavior.
experimental frame, which captures how the modeler's objectives impact on model construction, experimentation and validation. As we shall see later, in DEVJAVA experimental frames are formulated as model objects in the same manner as the models of primary interest. In this way, model/experimental frame pairs form coupled model objects with the same properties as other objects of this kind. It will become evident later, that this uniform treatment yields immediate benefits in terms of modularity and system entity structure representation.
Basic Entities and Relations (Conceptual framework underlying the DEVS formalism)
The basic objects are related by two relations:
modeling relation linking real system and model, defines how well the model represents the system or entity being modeled. In general terms a model can be considered valid if the data generated by the model agrees with the data produced by the real system in an experimental frame of interest.
simulation relation, linking model and simulator, represents how faithfully the simulator is able to carry out the instructions of the model. The basic items of data produced by a system or model are time segments. These time segments are mappings from intervals defined over a specified time base to values in the ranges of one or more variables. The variables can either be observed or measured.
Hierarchical Model Construction
A coupled model can be expressed as an equivalent basic model in the DEVS formalism. Such a basic model can itself be employed in a larger coupled model. This shows that the formalism is closed under coupling as required for hierarchical model construction. Expressing a coupled model as an equivalent basic model captures the means by which the components interact to yield the overall behavior.

The DEVS Formalism
At any time the system is in some state, s. If no external event occurs the system will stay in state s for time ta(s). Notice that ta(s) could be a real number as one would expect. But it can also take on the values 0 and infinity In the first case, the stay in state s is so short that no external events can intervene . we say that s is a transitory state. In the second case, the system will stay in s forever unless an external event interrupts its slumber. We say that s is a passive state in this case. When the resting time expires, i.e., when the elapsed time, e = ta(s), the system outputs the value, Ramda(s), and changes to state dint(s). Note output is only possible just before internal transitions.
If an external event (x is subset of X) occurs before this expiration time, i.e., when the system is in total state (s, e) with e < ta(s), the system changes to state dext(s,e,x). Thus the internal transition function dictates the system’s new state when no events have occurred since the last transition. While the external transition function dictates the system’s new state when an external event occurs. this state is determined by the input, x , the current state, s, and how long the system has been in this state, e, when the external event occurred. In both cases, the system is then is some new state s' with some new resting time, ta(s') and the same story continues.
DEVS in action (Interpretation of these elements)

Data Management Modeling for Distributed System
Fixed and Dynamic multiplexing
The multiplexed message size is constant in the fixed multiplexing. In the dynamic multiplexing, the message size varies with the number of active senders. Active sender indicates a sender which has an output in a certain time granule.
Fixed multiplexing with the predictive quantization
(SOH : the number of overhead bits for a packet; SQ: the quantized and encoded data bit size; Npair : the number of pair components; a: the ratio of active components)
The multiplexer collects the encoded bits and the active bits from each encoder. The encoded bits are the bits required to represent the message dimension alternatives. Let SQ be the number of the encoded bits. Then by:
However, the bits assigned for inactive senders can be wasted in fixed multiplexing. The fixed receiver de-multiplexer knows which sender sends certain encoded bits since the bit stream order in the multiplexed bits with fixed size follows a fixed ordering of the senders. Therefore, the additional bits representing which sender sends are not needed.
(SOH : the number of overhead bits for a packet; SQ: the quantized and encoded data bit size; SL: the encoded data bit size for sender ID; Npair : the number of pair components; a: the ratio of active components)
The dynamic sender multiplexer only collects the encoded bits from active senders. At a given event time, the number of active senders varies and the number of transmitted data bits is not fixed. Different from fixed multiplexing, additional bits (SL) are needed to represent active senders. The number of data bits for an active sender is calculated by adding the additional bits (log2 Npair < SL) and the encoded bits (SQ). Usually, a is less than 1 since all senders are not active senders at any given event time. The network loading for any global state transition of a sender federate using dynamic multiplexing is:
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