Energy-Efficient Routing in IoT Sensor Networks Using a Squirrel Optimization Algorithm-Based Clustering Framework

Abstract: Energy efficiency remains a major challenge in Internet of Things (IoT) sensor networks due to the limited battery capacity of sensor nodes. Inefficient routing strategies often lead to unbalanced energy consumption and early node failure. This paper proposes an energy-efficient routing framework based on the Squirrel Optimization Algorithm (SOA). In the proposed approach, SOA is employed to simultaneously optimize cluster head selection and routing path formation using a multi-objective fitness function considering residual energy, transmission distance, and network coverage. The algorithm balances exploration and exploitation to achieve optimal routing decisions while preventing premature energy depletion of critical nodes. Simulation results demonstrate that the proposed SOA-based routing method significantly improves network lifetime, residual energy distribution, and convergence speed compared with the Genetic Algorithm (GA). The results confirm that SOA provides an effective and scalable solution for energy-aware routing in IoT sensor networks.

Keywords: IoT Sensor Networks, Energy-Efficient Routing, Squirrel Optimization Algorithm, Metaheuristic Algorithms, Network Lifetime