3 research outputs found

    Optimal Coverage Control for Net-Drone Handvoer

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    The need for aerial network ensuring the stability of network at the specific area in which it is difficult to use network such as disaster area and rush hour is growing increasingly. However, the traditional aerial networks by UAV have problems such as limited battery for UAV, frequent handover by aerial environment and so on. These problems induce not only the fail of seamless handover but also a long handover time by frequent handover attempts. This paper presents an effective solution for resolving problems which are mentioned above. The main idea is to control the drone’s height and the distance between a drone and another drone. We also propose the seamless handover success probability and the false handover initiation probability to evaluate the optimal coverage decision algorithm. The simulation results using MATLAB show that the proposed algorithm operate to make the efficient handover compare with compare with conventional approach. The simulation also is conducted to compare the performance of the Optimal Coverage Decision algorithm by several elements. As a result, the proposed Optimal Coverage Decision algorithm guarantee the seamless handover and establish the one huge network by integrating the small networks. β“’ 2015 DGIST1.INTRODUCTION 2-- 2.BACKGROUND 4-- 2.1Net-Drone 4-- 2.2Wi-Fi Handover Procedure 6-- 2.3Mobile IP 7-- 3.NET-DRONE SEEN FROM 3D VIEW POINT 10-- 4.SEAMLESS HADNDOVER SUCCESS PROBABILITY AND FALSE HANDOVER INITIATION PROBABILITY 13-- 4.1Seamless handover success probability 13-- 4.2False handover Initiation probability 14-- 5.OPTIMAL COVERAGE DECISION ALGORITHM 15-- 6.SIMULATION 17-- 7.CONCLUSION 20인λ₯˜μ˜ ν™œλ™λ²”μœ„κ°€ 증가함에 따라 μ–Έμ œ μ–΄λ””μ„œλ‚˜ 보μž₯λ˜λŠ” 높은 톡신속도와 μ‹ ν˜Έ μ•ˆμ •μ„±μ— λŒ€ν•œ λ‹ˆμ¦ˆκ°€ μ¦κ°€ν•˜κ³  μžˆλ‹€. 이와같은 λ¬Έμ œμ— λŒ€ν•œ ν•œκ°€μ§€ μ†”λ£¨μ…˜μœΌλ‘œλŠ” λŸ¬μ‹œμ•„μ›Œμ™€ 같이 νŠΉμ • μ‹œκ°„λŒ€μ— 기쑴의 λ„€νŠΈμ›Œν¬κ°€ μ œλŒ€λ‘œ λ™μž‘ν•˜μ§€ λͺ»ν•˜λŠ” ν™˜κ²½μ—μ„œ μ‚¬μš©μžμ—κ²Œ μΌμ •ν•œ μˆ˜μ€€ μ΄μƒμ˜ λ„€νŠΈμ›Œν¬ μΊνŒ¨μ‹œν‹°λ₯Ό 보μž₯ν•˜κΈ° μœ„ν•΄ 곡쀑에 AP역할을 ν•˜λŠ” λ“œλ‘ μ„ λ„μ›Œ 곡쀑 λ„€νŠΈμ›Œν¬λ§μ„ κ΅¬μ„±ν•˜λŠ” 방법이 μžˆλ‹€. ν•˜μ§€λ§Œ μ΄λŸ¬ν•œ 방법은 λ‹€μŒκ³Ό 같은 문제점이 μ‘΄μž¬ν•œλ‹€. 첫 번째, λ“œλ‘ μ€ 무게의 μ œν•œ λ•Œλ¬Έμ— Wi-Fi AP둜만 μ‚¬μš©λ˜μ–΄μ§„λ‹€. μ΄λŸ¬ν•œ λ“œλ‘ μœΌλ‘œ κ΅¬μ„±λ˜λŠ” Wi-Fi λ„€νŠΈμ›Œν¬μ˜ 경우, μ…€λ£°λŸ¬λ§μ— λΉ„ν•΄ 쒁은 톡신 컀버리지와 μž¦μ€ ν•Έλ“œμ˜€λ²„ μ‹œλ„μ— μ˜ν•œ κΈ΄ ν•Έλ“œμ˜€λ²„ μ‹œκ°„μ„ κ°€μ Έ ν•΄λ‹Ή λ„€νŠΈμ›Œν¬λ₯Ό μ΄λ™ν•˜λŠ” μœ μ €μ˜ 연속적인 ν•Έλ“œμ˜€λ²„λ₯Ό μ–΄λ ΅κ²Œ λ§Œλ“ λ‹€. λ‘˜μ§Έ, 기쑴의 ν•Έλ“œμ˜€λ²„ κ²°μ • μ•Œκ³ λ¦¬μ¦˜μ—μ„œλŠ” AP의 컀버리지가 κ°™λ‹€κ³  κ°€μ •ν•œ 반면, μ‹€μ œ λ“œλ‘ μ˜ μ»€λ²„λ¦¬μ§€λŠ” μ£Όλ³€ μž₯μ• λ¬Όκ³Ό λŒν’κ³Ό 같은 μš”μΈμ— μ˜ν•œ κ²©λ ¬ν•œ λ“œλ‘ μ˜ 높이 변화에 μ˜ν•΄ λ‹€μ–‘ν•œ λ“œλ‘ μ˜ 컀버리지λ₯Ό κ°€μ Έ 기쑴의 ν•Έλ“œμ˜€λ²„ κ²°μ • μ•Œκ³ λ¦¬μ¦˜μ΄ μ‚¬μš©λ  수 μ—†λŠ” 문제점이 μ‘΄μž¬ν•œλ‹€. μ΄λŸ¬ν•œ 문제λ₯Ό ν•΄κ²°ν•˜κΈ° μœ„ν•΄ 이 λ…Όλ¬Έμ—μ„œλŠ” λ“œλ‘ μ˜ 높이와 λ“œλ‘ κ³Ό λ“œλ‘  μ‚¬μ΄μ˜ 거리λ₯Ό μ‘°μ ˆν•˜μ—¬ λŠμž„μ—†λŠ” ν•Έλ“œμ˜€λ²„λ₯Ό λ§Œμ‘±ν•˜λŠ” 졜적의 Wi-Fi 컀버리지λ₯Ό μ°ΎλŠ” RSS 기반의 Optimal Coverage Control μ•Œκ³ λ¦¬μ¦˜μ΄ μ œμ•ˆν•œλ‹€. μ΅œμ’…μ μœΌλ‘œ μš°λ¦¬λŠ” 이 λ…Όλ¬Έμ—μ„œ 곡쀑에 μ‘΄μž¬ν•˜λŠ” μž‘μ€ λ„€νŠΈμ›Œν¬λ“€μ„ ν•˜λ‚˜λ‘œ ν†΅ν•©ν•˜μ—¬ λ‹€μˆ˜μ˜ small Wi-Fi망을 ν†΅ν•©ν•˜μ—¬ μ‚¬μš©ν•˜λŠ” κΈ°μ—… λ‚΄ 톡신망과 같은 ν•˜λ‚˜μ˜ κ±°λŒ€ν•œ μ‹€μ™Έ Wi-Fi 망을 κ΅¬μΆ•ν•˜λŠ” 것을 λͺ©ν‘œλ‘œ ν•œλ‹€. β“’ 2015 DGISTMasterdCollectio

    A new FANET simulator for managing drone networks and providing dynamic connectivity

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    In the last decade, the attention on unmanned aerial vehicles has rapidly grown, due to their ability to help in many human activities. Among their widespread benefits, one of the most important uses regards the possibility of distributing wireless connectivity to many users in a specific coverage area. In this study, we focus our attention on these new kinds of networks, called flying ad-hoc networks. As stated in the literature, they are suitable for all emergency situations where the traditional networking paradigm may have many issues or difficulties to be implemented. The use of a software simulator can give important help to the scientific community in the choice of the right UAV/drone parameters in many different situations. In particular, in this work, we focus our main attention on the new ways of area covering and human mobility behaviors with the introduction of a UAV/drone behavior model to take into account also drones energetic issues. A deep campaign of simulations was carried out to evaluate the goodness of the proposed simulator illustrating how it works
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