• 한국인터넷방송통신학회논문지
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• 제11권6호
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• pp.31-39
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• 2011

재난현장에서 신속한 애드혹 무선 백본망을 형성하기 위해서는 사전계획 없이 초동 대응요원들에 의하여 무선 애드혹 중계장치를 실시간으로 배치하는 기법이 필요하다. 그러나 이를 실현하기 위해서는 중계장치의 중복배치 최소화뿐만 아니라 통신권역 확장을 위한 중계장치의 최적 위치를 선정할 수 있어야 한다. 따라서 본 논문에서는 통신권역을 최적화하기 위한 새로운 중계장치 배치기법을 제안하고 모의실험을 통하여 알고리즘의 성능이 향상되었음을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3120-3137
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• 2021

Small-sized IoT wireless sensing devices can be deployed with small aircraft such as drones, and the deployment of mobile IoT devices can be relocated to suit data collection with efficient relocation algorithms. However, the terrain may not be able to predict its shape. Mobile IoT devices suitable for these terrains are hopping devices that can move with jumps. So far, most hopping sensor relocation studies have made the unrealistic assumption that all hopping devices know the overall state of the entire network and each device's current state. Recent work has proposed the most realistic distributed network environment-based relocation algorithms that do not require sharing all information simultaneously. However, since the shortest path-based algorithm performs communication and movement requests with terminals, it is not suitable for an area where the distribution of obstacles is uneven. The proposed scheme applies a simple Monte Carlo method based on relay nodes selection random variables that reflect the obstacle distribution's characteristics to choose the best relay node as reinforcement learning, not specific relay nodes. Using the relay node selection random variable could significantly reduce the generation of additional messages that occur to select the shortest path. This paper's additional contribution is that the world's first distributed environment-based relocation protocol is proposed reflecting real-world physical devices' characteristics through the OMNeT++ simulator. We also reconstruct the three days-long disaster environment, and performance evaluation has been performed by applying the proposed protocol to the simulated real-world environment.