Findings validate the efficacy of incorporating swarm intelligence into the 5G architectures as a viable and self-optimizing solution for the promotion of connectivity and signal power performance in the next-generation high-density wireless networks.
H. Lasisi, H. B. Omodeni, B. Aderinkola et al.· 0 citations
Bio-inspired routing algorithms have gained significant attention as effective approaches for solving complex optimization problems in modern communication networks. Drawing inspiration from collective behaviors in nature, these methods have been widely applied in decentralized environments such as wireless sensor and...
Spasimir Varshilov, K. Nikolova· International Scientific Con...· 0 citations
Comparison shows that, under the evaluated DeepMIMO-based scenarios, the examined assignment-based methods exhibit different trade-offs in throughput, energy-consumption-related performance, bandwidth utilization, and adaptability to varying user demands, offering useful insights for 5G MIMO resource allocation studies...
Nikolaos Prodromos, Damianos Diasakos, V. Kokkinos et al.· Wireless personal communicat...· 0 citations
This work aims to design an efficient framework by incorporating a novel hybrid metaheuristic algorithm that combines Draco Lizard Optimization (DLO) and Sand Cat Optimization (SCO) for optimal task offloading and resource allocation for IoT applications.
The economic scheduling of grid-connected microgrids requires the coordinated dispatch of renewable energy sources, controllable distributed generators, battery energy storage systems, and power exchange with the utility grid while satisfying various operational constraints. Owing to the time-varying nature of renewabl...
The proposed GWO-EAOMDV framework outperforms both traditional EAOMDV and alternative optimization-based routing protocols and reduces end-to-end latency by 15-22% while simultaneously enhancing PDR by 12-18% and improving energy efficiency.
S. Hemasri, R. A.· International Research Journ...· 0 citations
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