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FANET optimization: a destination path flow model
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Closed-loop routing in flying ad hoc networks (FANET) arises as a result of the quick changes of communication links and topology. As such, causing link breakage during information dissemination. This paper proposed a destination path flow model to improve the communication link in FANET. The models utilized Smell Agent Optimization and Particle Swarm Optimization algorithms in managing link establishment between communicating nodes. The modeled scenario depicts the practical application of FANET in media and sports coverage where only one vendor is given the license for live coverage and must relay to other vendors. Three different scenarios using both optimization Algorithms were presented. From the result obtained, the SAO optimizes the bandwidth costs much better than PSO with a percentage improvement of 10.46%, 4.04% and 3.66% with respect to the 1st, 2nd and 3rd scenarios respectively. In the case of communication delay between the FANET nodes, the PSO has a much better communication delay over SAO with percentage improvement of 40.89%, 50.26% and 68.85% in the first, second and third scenarios respectively.
Institute of Advanced Engineering and Science
Title: FANET optimization: a destination path flow model
Description:
Closed-loop routing in flying ad hoc networks (FANET) arises as a result of the quick changes of communication links and topology.
As such, causing link breakage during information dissemination.
This paper proposed a destination path flow model to improve the communication link in FANET.
The models utilized Smell Agent Optimization and Particle Swarm Optimization algorithms in managing link establishment between communicating nodes.
The modeled scenario depicts the practical application of FANET in media and sports coverage where only one vendor is given the license for live coverage and must relay to other vendors.
Three different scenarios using both optimization Algorithms were presented.
From the result obtained, the SAO optimizes the bandwidth costs much better than PSO with a percentage improvement of 10.
46%, 4.
04% and 3.
66% with respect to the 1st, 2nd and 3rd scenarios respectively.
In the case of communication delay between the FANET nodes, the PSO has a much better communication delay over SAO with percentage improvement of 40.
89%, 50.
26% and 68.
85% in the first, second and third scenarios respectively.
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