Dynamic topology reconstruction protocol for UAV swarm networking :

박민수

추천

검색

자료유형: 학위논문

저자정보: 박민수 (경희대학교, Kyung Hee University)

지도교수: Sungwon Lee

발행연도: 2020

저작권: 경희대학교 논문은 저작권에 의해 보호받습니다.

이용수3

초록· 키워드

4차 산업혁명과 더불어 UAV(Unmanned Aerial Vehicle)은 지난 10년간 매우 빠르게 성장하였다. 이러한 성장과 함께 다양한 분야에서 UAV를 활용한 연구들이 진행되고 있다. UAV는 한 기의 기체만 운용하는 경우보다 여러 기의 기체를 활용할 경우 더 경제적이고 효과적이다. 일반적으로 UAV는 데이터를 수집하고 그 정보를 Control Center로 전송하고 Control Center로 부터 제어 명령을 받아 행동한다. 이때 UAV와 Control Center 간의 통신은 주로 RF, Bluetooth, Wi-Fi, Cellular 등의 module을 이용하여 이루어진다. 하지만 여러 대의 UAV가 Control Center와 직접적으로 통신하게 되는 경우 통신 기술들의 한계점과 노드가 증가할 경우 생기는 문제점 등이 발생하게 된다. 이러한 점들을 해결하기 위한 연구들이 진행되었다. 여러 연구들에서 UAV들의 ad-hoc network를 구성하여 Wi-Fi,Bluetooth의 통신 범위의 제약이나 cellular의 고비용 문제를 해결하였다. 하지만 기존의 연구들은 ad-hoc network의 고정된 topology를 구성하였다. 이러한 연구들은 UAV의 빠른 이동성과 잦은 대형변경으로 인한 네트워크 토폴로지의 변경 문제점을 해결하지 못하였다. 이는 UAV의 대형 변경을 고려하지 않아 구성된 토폴로지의 대형으로만 이동해야 하는 한계점이 존재하였다.
본 논문에서는 이를 해결하기 위해 UAV Swarm의 동적인 토폴로지 구성 프로토콜에 대해 제안한다. 본 논문의 주요 내용은 다음과 같다. 먼저 기존의 UAV 통신에 대한 연구와 한계점에 대해 알아본 후 이를 해결하기 위한 프로토콜을 제시한다. 본 논문에서 제안하는 것은 여러 대의 UAV를 이용하여 미션을 수행하려 할 때 해당 UAV들이 어떻게 Ad-hoc Network를 구성하는 지에 대한 프로토콜이다. 또한 Network를 구성한 후 비행 대형의 변경으로 인해 Network Topology가 변경되었을 때 변화한 네트워크 토폴로지가 어떤 과정을 통해 재구성되는지에 대해 설명한다. 마지막으로 상황을 설정하고 제안한 프로토콜을 적용하여 그에 대한 실험을 진행한다. 이후 그에 대한 결과를 분석하고 향후 필요한 연구에 대해 기술한다.

Along with the fourth industrial revolution, the Unmanned Aerial Vehicle (UAV) has grown very rapidly over the past decade. With this rapid growth, studies using UAVs are underway in various areas. UAVs are more economical and effective when utilizing several nodes than if only one aircraft is operated. In general, UAVs collect data and transmit that information to the control center and act on control commands from the control center. Communication between UAV and control center is usually done using modules such as RF, Bluetooth, Wi-Fi, and Cellular. However, when multiple UAVs communicate directly with the control center, the limitations of communication technologies and problems with increasing nodes occur. To address these points, several studies have constructed the ad-hoc network of UAVs to address limitations of Wi-Fi and Bluetooth communication range, or the high cost problem of Cellular system. However, previous studies have constructed fixed topology of ad-hoc network. These studies did not take into account the problem of changing the network topology due to the rapid mobility and frequent formation changes of UAVs. Because of that, the limits occurred that UAVs moved only in pre-built topology
In this paper, we propose the dynamic topology construction protocol of UAV Swarm to address this problem. The main contents of this paper are as follows. We first look at the research and limitations of existing UAV communications. And propose a protocol to solve this problem. What is proposed in this paper is a protocol for how UAVs construct ad-hoc networks when trying to perform missions using multiple UAVs. And also describes how the changed network topology is reconstructed when network topology changes due to changes in flight formation. Finally, set up the situation and apply the proposed protocol to proceed with the experiment. And analyze about the results and describe further required research.

Abstract ····································································································
1. Introduction ························································································· 1
2. Related Works ······················································································ 3
2.1 UAV Wireless Communications ························································· 3
2.2 UAV Swarm Research ···································································· 5
2.3 Mobile Ad Hoc Network ································································· 5
3. Proposal ······························································································ 7
3.1 Dynamic Topology Reconstruction Protocol ········································· 7
3.1.1 Goal of DTRP ········································································· 8
3.1.2 Architecture and Components of DTRP ··········································· 7
3.2 Topology Reconstruction using DTRP ················································· 8
3.2.1 The Entire Process ··································································· 8
3.2.2 Base Topology Reconstruction Process ··········································· 8
3.2.3 Power On Registration ······························································ 10
3.2.4 Periodic Check Operation ·························································· 10
3.2.5 Control Commands Offer & Operation ··········································· 11
3.3 Message Format for a DTRP ···························································· 12
3.3.1 Init Message ·········································································· 12
3.3.2 Link Message ········································································ 12
3.3.3 ACK ·················································································· 12
3.3.4 Link Check Message ································································ 13
3.3.5 Error Message ······································································· 13
3.3.6 Control Offer & Operation Message ·············································· 13
4. Result ······························································································· 14
4.1 Simulation Environment ································································· 14
4.2 Testbed Scenario ·········································································· 16
4.2.1 Base Case ············································································· 16
4.2.2 Test Case 1 ··········································································· 18
4.2.3 Test Case 2 ··········································································· 19
4.2.4 Total Number of Messages per Case ·············································· 21
4.3 Comparison between Central Control System and Proposed System ·············· 22
5. Conclusion ························································································· 23
6. References ··························································································· 24

최근 본 자료

전체보기

구분	그룹	데이터 항목
AI 학습용 데이터	원문	원문 PDF 파일
AI 학습용 데이터	원문 + 메타 (기본/상세)	원문 PDF 파일 및 서지정보 CSV
대량 구매용 데이터	B2B 구독 방식	특정 자료 한정으로 원문 접근 권한 부여
대량 구매용 데이터	URL 전달 방식	바로 PDF 뷰어를 열람할 수 있는 URL 제공

구분	그룹	데이터 항목
AI 학습용 데이터	기본 메타	발행기관명, 간행물명, 권호명, 권(vol), 호(issue), 통권, 발행연도, 발행월, 논문명, 저자명, 시작페이지, 종료페이지, 전체페이지, 상세페이지URL
상세 메타 데이터	발행기관 메타	발행기관 이명, 영문명, 창립연도, 홈페이지URL, 발행기관 소개
	간행물 메타	부제목, 간행물 유형, ISSN, ISBN, 최초발행연도, 폐간연도, 간행빈도, 발행주기, 등재사항, 이용수, 피인용수, 권호수, 논문수, 표지이미지
	논문 메타	작성 언어, 부제목, 대등제목, 목차, 키워드, 초록, 이미지, 참고문헌, 이용수, 피인용수, 논문활용도, DBpia통합주제분류, KDC분류, DDC분류, 한국연구재단분류, UCI, DOI
	저자 메타	소속기관, 소속부서, 직급, 연구분야, 연구키워드, 이용수, 피인용수, 저자 논문활용도

구분	그룹	데이터 항목
※ 결합형/맞춤형 메타 데이터는 신청 내용에 따라 다양하게 제공 가능
이용순위 정보	주제분야별 많이 이용된 논문	“인문학”에서 많이 이용된 논문 TOP100
	이용기관별 많이 이용된 논문	“중고등학교”에서 많이 이용된 논문 TOP100
	세부기관별 많이 이용된 논문	“서울대학교”에서 많이 이용된 논문 TOP100
	키워드별 많이 이용된 논문	“Chat GPT”에서 많이 이용된 논문 TOP100
키워드 정보	많이 이용된 키워드	특정기간/분야/저널 내 많이 이용된 키워드
	많이 발행된 키워드	특정기간/분야/저널 내 많이 발행된 키워드
	많이 검색된 키워드	특정기간/분야/저널 내 많이 검색된 키워드
	연구 트렌드 키워드	특정 키워드 연관 연구동향 분석 데이터 키워드

논문 기본 정보

초록· 키워드

목차

최근 본 자료

댓글(0)