Analytical evaluation shows improved performance of swarm fission optimisation in wireless networks, suggesting better resource management.
The wireless communication network spectrum is a limited resource. With the rapid growth of mobile communication services in recent years, traditional spectrum allocation methods - typically based on fixed spectrum allocation strategies - often lead to inefficient and uneven resource distribution. Consequently, there is an urgent need to address the issues of spectrum allocation and optimisation. The integration of semantic mobile computing within the Internet of Things (IoT), along with advancements in emerging bionic models, offers novel approaches to this challenge. Analytical results indicate that, in terms of performance, the success rate of the Swarm Fission Optimisation Algorithm (SFOA) surpasses that of the particle swarm optimisation (PSO) algorithm, with both achieving a 100% success rate in function evaluations. Furthermore, the SFOA algorithm demonstrates superior stability and accuracy compared to the other two algorithms. Its advantages become particularly pronounced under high signal-to-noise ratio (SNR) conditions.
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Palanikumar et al. (2026) studied this question.
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