A Dynamic Clustering Mechanism With Load-Balancing for Flying Ad Hoc Networks

被引:16
作者
Asaamoning, Godwin [1 ,2 ]
Mendes, Paulo [3 ,4 ]
Magaia, Naercio [1 ,5 ]
机构
[1] Univ Lusofona, COPELABS, P-1749024 Lisbon, Portugal
[2] Bolgatanga Tech Univ, Sch Appl Sci & Arts, Sumbrungu 09648505, UB, Ghana
[3] Univ Lusofona, Sch Commun Architecture Arts & Informat Technol, P-1749024 Lisbon, Portugal
[4] Airbus Cent Res & Technol, D-82024 Munich, Germany
[5] Univ Sussex, Sch Engn & Informat, Brighton BN1 9QJ, E Sussex, England
关键词
Routing; Heuristic algorithms; Ad hoc networks; Topology; Routing protocols; Optimization; Delays; FANET; dynamic clustering; load-balancing; routing; ROUTING PROTOCOL; OPTIMIZATION; MOBILITY;
D O I
10.1109/ACCESS.2021.3130417
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Flying Ad Hoc NETworks (FANETs) are expected to have a significant impact in several use-cases, from smart agriculture and cities, to mission critical scenarios. The recent surge in the use of FANETs is motivated by their adaptable and flexible behaviours in different scenarios (e.g. disaster-hit locations) allowing the usage of services that require information from remote locations, such as for assessment of damages, checking for survivors, or providing onsite views to assist rescue teams. While FANETs have been developed to provide such critical services, disseminating data with proper performance faces challenges due to inherent properties of FANETs, namely frequent wireless disconnections, intermittent available nodes, and dynamic topologies, mostly when facing an increasing number of deployed unmanned aerial vehicles. Aiming to tackle these challenges, we propose a new Dynamic Clustering Mechanism with Load-Balancing able to support efficient dissemination of data packets in FANETs while ensuring good reliability and scalability factors. The proposed solution is based on the combination of a new meta-heuristic optimization scheme, known as Political Optimizer, used to perform clustering while addressing limitations caused by topology changes, and a new Shannon entropy function implemented to address cluster fault tolerance and traffic overloads. Simulation results show that by combining our proposed model with standard position-based routing protocols, a higher number of end-to-end transmissions are ensured, while supporting an average packet delivery ratio of 97%, an average end-to-end delay of 0.225 seconds, and an average power consumption 37% lower than other state-of-the-art clustering protocols.
引用
收藏
页码:158574 / 158586
页数:13
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