TY - GEN
T1 - An Efficient Geometric-Partition-Based Distributed Algorithm for Detecting Critical Nodes in Flying Ad-Hoc Networks
AU - Liu, Yongchao
AU - Lei, Lei
AU - Zhang, Lijuan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - In FANETs, failure of any critical node (cut vertex) separates the networks into disconnected components, resulting in a degradation of connectivity reliability. Therefore, it is crucial to detect the critical nodes to ensure connectivity maintenance in FANETs. Since the existing distributed approaches for detecting critical nodes still suffer from high overhead and low accuracy, this paper proposes an efficient geometric-partition-based distributed algorithm for detecting critical nodes using a novel partitioned framework and geometric theory. The proposed algorithm is divided into two phases, the first phase can detect most of the nodes under the partitioned framework using local neighbor information, the second phase further detects the remaining nodes by identifying geometric cycles formed between these nodes. The simulation results reveals that the proposed algorithm further improves the accuracy, can detect critical nodes in large scale networks more efficiently than existing distributed algorithms, with lower energy consumption and faster speed.
AB - In FANETs, failure of any critical node (cut vertex) separates the networks into disconnected components, resulting in a degradation of connectivity reliability. Therefore, it is crucial to detect the critical nodes to ensure connectivity maintenance in FANETs. Since the existing distributed approaches for detecting critical nodes still suffer from high overhead and low accuracy, this paper proposes an efficient geometric-partition-based distributed algorithm for detecting critical nodes using a novel partitioned framework and geometric theory. The proposed algorithm is divided into two phases, the first phase can detect most of the nodes under the partitioned framework using local neighbor information, the second phase further detects the remaining nodes by identifying geometric cycles formed between these nodes. The simulation results reveals that the proposed algorithm further improves the accuracy, can detect critical nodes in large scale networks more efficiently than existing distributed algorithms, with lower energy consumption and faster speed.
KW - Critical Nodes Detection
KW - Flying Ad-Hoc Networks (FANETs)
KW - Geometric Partitioned Framework
UR - http://www.scopus.com/inward/record.url?scp=85192448526&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-2757-5_32
DO - 10.1007/978-981-97-2757-5_32
M3 - Conference contribution
AN - SCOPUS:85192448526
SN - 9789819727568
T3 - Lecture Notes in Electrical Engineering
SP - 303
EP - 311
BT - Proceedings of the 2nd International Conference on Internet of Things, Communication and Intelligent Technology
A2 - Dong, Jian
A2 - Zhang, Long
A2 - Cheng, Deqiang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Internet of Things, Communication and Intelligent Technology, IoTCIT 2023
Y2 - 22 September 2023 through 24 September 2023
ER -