TY - GEN
T1 - Performance Optimization of NLSR's Routing Protocol Paramters in Flying Ad Hoc Networks
AU - Liu, Zhoujie
AU - Zhang, Yu
AU - Li, Tong
AU - Li, Zhenghan
AU - Diao, Wenlan
AU - Wang, Yiming
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - In recent years, Flying Ad Hoc Network (FANET) has been increasingly adopted in civil and military applications owing to its flexibility. However, the topology of FANET is highly dynamic, which poses significant challenges for routing protocol of FANET. Named Data Networking (NDN), as the most popular content-centric network architecture, provides enhanced support for high dynamic topology. Within the current NDN architecture, the Named data link state routing (NLSR) protocol is widely utilized. There are many routing protocol parameters in the NLSR protocol, such as hello interval, hello timeout, and synchronization period, which are scenario dependent and have a significant impact on the performance of FANET. It is necessary to find the optimal routing protocol parameters of different scenarios to achieve the best balance between the overhead of the routing protocol and its responsiveness to dynamic topology. This article derives the collision probability based on the Bianchi model, estimates the average path length (APL) based on the Erdös-Renyi random network assumption, and models the network throughput based on the collision probability and APL. By maximizing the throughput of application layer, the optimal routing protocol parameters are derived and the NLSR with the optimal parameters is called OP-NLSR. The simulation is conducted in ndnSIM to compare the throughput under different routing protocol parameters. The simulation results show that OP-NLSR can achieve 10% throughput improvement compared to NLSR with default configurations.
AB - In recent years, Flying Ad Hoc Network (FANET) has been increasingly adopted in civil and military applications owing to its flexibility. However, the topology of FANET is highly dynamic, which poses significant challenges for routing protocol of FANET. Named Data Networking (NDN), as the most popular content-centric network architecture, provides enhanced support for high dynamic topology. Within the current NDN architecture, the Named data link state routing (NLSR) protocol is widely utilized. There are many routing protocol parameters in the NLSR protocol, such as hello interval, hello timeout, and synchronization period, which are scenario dependent and have a significant impact on the performance of FANET. It is necessary to find the optimal routing protocol parameters of different scenarios to achieve the best balance between the overhead of the routing protocol and its responsiveness to dynamic topology. This article derives the collision probability based on the Bianchi model, estimates the average path length (APL) based on the Erdös-Renyi random network assumption, and models the network throughput based on the collision probability and APL. By maximizing the throughput of application layer, the optimal routing protocol parameters are derived and the NLSR with the optimal parameters is called OP-NLSR. The simulation is conducted in ndnSIM to compare the throughput under different routing protocol parameters. The simulation results show that OP-NLSR can achieve 10% throughput improvement compared to NLSR with default configurations.
KW - Bianchi model
KW - Flying ad-hoc network (FANET)
KW - Named Data Networking (NDN)
KW - component
KW - routing parameter
UR - https://www.scopus.com/pages/publications/105010824609
U2 - 10.1109/ISEAE64934.2025.11042207
DO - 10.1109/ISEAE64934.2025.11042207
M3 - Conference contribution
AN - SCOPUS:105010824609
T3 - 2025 7th International Conference on Information Science, Electrical and Automation Engineering, ISEAE 2025
SP - 699
EP - 703
BT - 2025 7th International Conference on Information Science, Electrical and Automation Engineering, ISEAE 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Information Science, Electrical and Automation Engineering, ISEAE 2025
Y2 - 18 April 2025 through 20 April 2025
ER -