The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
드론 떼는 여러 드론이 협력하여 임무를 수행하는 로봇 아키텍처입니다. 요즘에는 소수의 게이트웨이 드론(GW)이 프로토콜 변환기 역할을 하여 독립적인 무선 프로토콜을 사용하는 여러 떼의 혼합을 가능하게 하는 이종 드론 떼가 많은 연구자들로부터 많은 주목을 받고 있습니다. 우리의 이전 작업이 제안되었습니다 경로 최적화 — 각 통신 요청에 대해 네트워크에 지름길을 만들기 위해 GW를 자율적으로 재배치함으로써 이기종 드론 떼를 사용하는 원격 비디오 모니터링 시스템에서 엔드 투 엔드 경로 홉 수를 최소화하는 방법입니다. 하지만, 경로 최적화 GW 수보다 많은 비디오 세션을 동시에 요청하는 경우 통신 품질을 향상시키는 데 한계가 있습니다. 경로 코디네이터본 논문에서 제안하는 는 모든 GW의 협력적이고 동기적인 재배치를 도입하여 세션 수에 관계없이 end-to-end 홉의 균일한 감소를 달성하고 허용 가능한 홉 만족률을 최대화합니다. 경로 코디네이터 두 단계로 구성됩니다. 첫째, 모든 GW를 지리적으로 재배치하여 물리적 최적화를 수행하고(재배치 단계), 다음으로 각 비디오 흐름의 중계 GW를 수정하여 논리적 최적화를 수행합니다(재라우팅 단계). 컴퓨터 시뮬레이션을 통해 밝혀진 사실 경로 코디네이터 다양한 환경에 적응하고 기대한 만큼의 성능을 발휘합니다. 게다가 그 성능은 무차별 대입 검색으로 가능한 상한선과 비슷합니다.
Taichi MIYA
Tokyo Institute of Technology
Kohta OHSHIMA
Tokyo University of Marine Science and Technology
Yoshiaki KITAGUCHI
Tokyo Institute of Technology
Katsunori YAMAOKA
Tokyo Institute of Technology
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부
Taichi MIYA, Kohta OHSHIMA, Yoshiaki KITAGUCHI, Katsunori YAMAOKA, "Adaptive GW Relocation and Strategic Flow Rerouting for Heterogeneous Drone Swarms" in IEICE TRANSACTIONS on Communications,
vol. E106-B, no. 4, pp. 331-351, April 2023, doi: 10.1587/transcom.2022EBP3091.
Abstract: A drone swarm is a robotic architecture having multiple drones cooperate to accomplish a mission. Nowadays, heterogeneous drone swarms, in which a small number of gateway drones (GWs) act as protocol translators to enable the mixing of multiple swarms that use independent wireless protocols, have attracted much attention from many researchers. Our previous work proposed Path Optimizer — a method to minimize the number of end-to-end path-hops in a remote video monitoring system using heterogeneous drone swarms by autonomously relocating GWs to create a shortcut in the network for each communication request. However, Path Optimizer has limitations in improving communication quality when more video sessions than the number of GWs are requested simultaneously. Path Coordinator, which we propose in this paper, achieves a uniform reduction in end-to-end hops and maximizes the allowable hop satisfaction rate regardless of the number of sessions by introducing the cooperative and synchronous relocation of all GWs. Path Coordinator consists of two phases: first, physical optimization is performed by geographically relocating all GWs (relocation phase), and then logical optimization is achieved by modifying the relaying GWs of each video flow (rerouting phase). Computer simulations reveal that Path Coordinator adapts to various environments and performs as well as we expected. Furthermore, its performance is comparable to the upper limits possible with brute-force search.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2022EBP3091/_p
부
@ARTICLE{e106-b_4_331,
author={Taichi MIYA, Kohta OHSHIMA, Yoshiaki KITAGUCHI, Katsunori YAMAOKA, },
journal={IEICE TRANSACTIONS on Communications},
title={Adaptive GW Relocation and Strategic Flow Rerouting for Heterogeneous Drone Swarms},
year={2023},
volume={E106-B},
number={4},
pages={331-351},
abstract={A drone swarm is a robotic architecture having multiple drones cooperate to accomplish a mission. Nowadays, heterogeneous drone swarms, in which a small number of gateway drones (GWs) act as protocol translators to enable the mixing of multiple swarms that use independent wireless protocols, have attracted much attention from many researchers. Our previous work proposed Path Optimizer — a method to minimize the number of end-to-end path-hops in a remote video monitoring system using heterogeneous drone swarms by autonomously relocating GWs to create a shortcut in the network for each communication request. However, Path Optimizer has limitations in improving communication quality when more video sessions than the number of GWs are requested simultaneously. Path Coordinator, which we propose in this paper, achieves a uniform reduction in end-to-end hops and maximizes the allowable hop satisfaction rate regardless of the number of sessions by introducing the cooperative and synchronous relocation of all GWs. Path Coordinator consists of two phases: first, physical optimization is performed by geographically relocating all GWs (relocation phase), and then logical optimization is achieved by modifying the relaying GWs of each video flow (rerouting phase). Computer simulations reveal that Path Coordinator adapts to various environments and performs as well as we expected. Furthermore, its performance is comparable to the upper limits possible with brute-force search.},
keywords={},
doi={10.1587/transcom.2022EBP3091},
ISSN={1745-1345},
month={April},}
부
TY - JOUR
TI - Adaptive GW Relocation and Strategic Flow Rerouting for Heterogeneous Drone Swarms
T2 - IEICE TRANSACTIONS on Communications
SP - 331
EP - 351
AU - Taichi MIYA
AU - Kohta OHSHIMA
AU - Yoshiaki KITAGUCHI
AU - Katsunori YAMAOKA
PY - 2023
DO - 10.1587/transcom.2022EBP3091
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E106-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2023
AB - A drone swarm is a robotic architecture having multiple drones cooperate to accomplish a mission. Nowadays, heterogeneous drone swarms, in which a small number of gateway drones (GWs) act as protocol translators to enable the mixing of multiple swarms that use independent wireless protocols, have attracted much attention from many researchers. Our previous work proposed Path Optimizer — a method to minimize the number of end-to-end path-hops in a remote video monitoring system using heterogeneous drone swarms by autonomously relocating GWs to create a shortcut in the network for each communication request. However, Path Optimizer has limitations in improving communication quality when more video sessions than the number of GWs are requested simultaneously. Path Coordinator, which we propose in this paper, achieves a uniform reduction in end-to-end hops and maximizes the allowable hop satisfaction rate regardless of the number of sessions by introducing the cooperative and synchronous relocation of all GWs. Path Coordinator consists of two phases: first, physical optimization is performed by geographically relocating all GWs (relocation phase), and then logical optimization is achieved by modifying the relaying GWs of each video flow (rerouting phase). Computer simulations reveal that Path Coordinator adapts to various environments and performs as well as we expected. Furthermore, its performance is comparable to the upper limits possible with brute-force search.
ER -