• Title/Summary/Keyword: Swam Intelligence

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A Routing Method Using Swarm Intelligence in MANETs (MANET에서 군집지능을 이용한 라우팅 방안)

  • Woo, Mi-Ae;Dong, Ngo Huu;Roh, Woo-Jong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.7B
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    • pp.550-556
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    • 2008
  • Swam intelligence refers that a large group of simple and unsophisticated entities work together to achieve complex and significant tasks. Researches using such swarm intelligence has been performed in the network routing area. Expecially, it has been well known that routing in mobile ad-hoc networks whose features are dynamic topology and routing based on the local information is one of the applications of swarm intelligence. In this paper, we propose an ant-based routing method for MANET. The proposed method sets its goals to reduce overheads by managing ants efficiently, and to reduce route set up time. The results obtained from simulations proved that the proposed method provides shorter path set-up time and end-to-end delay and less overhead while providing comparable packet delivery ratio.

A Digital Twin Simulation Model for Reducing Congestion of Urban Railways in Busan (부산광역시 도시철도 혼잡도 완화를 위한 디지털 트윈 시뮬레이션 모델 개발)

  • Choi, Seon Han;Choi, Piljoo;Chang, Won-Du;Lee, Jihwan
    • Journal of Korea Multimedia Society
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    • v.23 no.10
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    • pp.1270-1285
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    • 2020
  • As a representative concept of the fourth industrial revolution era where everything is digitized, digital twin means analyzing and optimizing a complex system using a simulation model synchronized with the system. In this paper, we propose a digital twin simulation model for the efficient operation of urban railways in Busan. Due to the geopolitical nature of Busan, where there are many mountains and narrow roads, the railways are more useful than other public transportation. However, this inversely results in a high level of congestion, which is an inconvenience to citizens and may be fatal to the spread of the virus, such as COVID19. Considering these characteristics, the proposed model analyzes the congestion level of the railways in Busan. The model is developed based on a mathematical formalism called discrete-event system specification and deduces the congestion level and the average waiting time of passengers depending on the train schedule. In addition, a new schedule to reduce the congestion level is derived through particle swarm optimization, which helps the efficient operation of the railways. Although the model is developed for the railways in Busan, it can also be used for railways in other cities where a high level of congestion is a problem.