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A Bio-Inspired Energy-Aware Routing Mechanism for Flying Ad-hoc Networks

Chehelmardian, Farnaz | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57968 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Afshin Hemmatyar, Ali Mohammad; Safaei, Bardia
  7. Abstract:
  8. Nowadays, adaptable, versatile and flexible nature of Flying ad-hoc Networks (FANETs) make them popular in many academic and practical fields such as real-time applications, civil applications, search and rescue operations, identification and logistics. FANETs are organized multi-UAV systems that can accomplish complex missions through cooperation and collaboration. The unique features of these networks, such as high mobility, low node density, high frequency of topology changes, and three-dimensional flight environment, create various challenges in communication, especially in packet routing. In this type of network, a subset of UAVs connects to the infrastructure, while the remaining UAVs use inter-UAV communication to connect to the ground control station or satellite. Therefore, preserving the energy of nodes is crucial for improving overall performance, increasing reliability, longevity, and cost efficiency of the network. Traditional routing protocols often do not adequately address the specific challenges of FANETs, whereas nature-inspired optimization algorithms have shown suitable performance due to their adaptability to network dynamics, distributed decision-making, and scalability in solving many similar issues. These algorithms offer an efficient solution, by mimicking the swarm intelligence found in nature. The Jellyfish Optimization Algorithm (JOA) is based on a set of rules derived from simulating the behavior of jellyfish in the ocean. The algorithm uses a combination of deterministic and random movements to explore the search space and exploit suitable solutions. This method performs well in high-dimensional search spaces and can manage multiple objectives and constraints with general exploration capability and robustness. In this context, this research presents a routing method based on the Jellyfish Optimization Algorithm, aiming to improve energy consumption for FANETs. Simulation results indicate the superiority of the proposed method compared to previous approaches, particularly in terms of energy consumption. Compared to LBOPAR, OPAR and IABC algorithm, the proposed method results in average improvement in packet delivery rate and a 30-36% improvement in network throughput. Additionally, with a 24% reduction in delay and a 30% improvement in average node energy, the JFF method is a suitable option for FANET routing. This performance indicates an improvement in the quality of service and network efficiency
  9. Keywords:
  10. Routing Algorithm ; Energy Efficient Routing ; Energy Efficiency ; Bioinspired Design ; Swarm Intelligence ; Flying Ad-Hoc Networks ; Jellyfish Search Optimization

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