Wireless Routing Using Automata Theory and Formal Language
Keywords:
Wireless Sensor Networks, Routing, Automata Theory, Cellular Automata, Learning Automata, Cluster Head Selection, Gateway SelectionAbstract
In wireless sensor networks (WSNs), routing is still a major problem that affects network longevity, energy consumption, and data transmission efficiency. The explicit modeling of cluster head (CH) and gateway assignments to successfully balance efficiency and adaptability has received relatively little attention, despite the fact that the majority of current research focuses on either network coverage optimization or adaptive routing path optimization. The current study fills this gap by presenting a novel routing architecture based on finite automata theory that is intended to dynamically manage gateway assignments and CH in clustered WSNs. The suggested system makes use of deterministic and non-deterministic finite automata (DFA and NFA) to enable energy-conscious, adaptive reactions to variations in resource availability and network structure. Comprehensive simulations and comparative analyses against existing Cellular Automata (CA) and Learning Automata (LA) methods demonstrate superior scalability, reduced complexity, and enhanced network lifetime. By integrating theoretical automata insights with practical routing requirements, this study provides a strong foundation for future large-scale WSN management.
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