Quality of service improvement in fiber-wireless networks using a fuzzy-based nature-inspired algorithm

Fiber-Wireless (Fi-Wi) networks attract interest as a dependable communication backbone in several additional applications. The cheap cost, dependability, accessibility of Wireless Sensor Networks, and optical fiber networks’ high bandwidth and reliability contribute to it. Although Fi-Wi networks supply good delay performance, they may not be able to fulfill the needs of the smart grid delay-critical applications mentioned earlier. Since the Quality of Service (QoS) is a prerequisite for deploying high-speed Fi-Wi broadband access networks, it is critical to identify and address common issues (such as bandwidth and latency) in high-speed next-generation networks. This study offers a unique strategy for improving QoS in Fi-Wi networks based on a fuzzy-based Cat Swarm Optimization (CSO) algorithm. CSO is a strong metaheuristic swarm-based optimization technique that has garnered a lot of favorable comments since its inception. CSO is a resilient and strong meta-heuristic algorithm based on cat behavior. It has two search modes: seeking and tracing, which may be combined using the mixing ratio parameter. The suggested solution reduces energy usage, packet loss, and latency, according to simulation findings using the MATLAB program. Compared to previous methods, simulations reveal that the suggested method produces relatively excellent outcomes and has a higher performance.