# Enhanced Secretary Bird Optimization Algorithm for Energy-Efficient Cluster Head Selection in Wireless Sensor Networks

## TL;DR

This paper introduces an improved optimization algorithm to select cluster heads in wireless sensor networks, enhancing energy efficiency and network lifetime.

## Contribution

The novel contribution is the Enhanced Secretary Bird Optimization Algorithm (ESBOA) with logistic chaotic initialization and iterative local search for better energy-aware clustering.

## Key findings

- ESBOA outperforms standard algorithms in preserving alive nodes and residual energy.
- The algorithm extends network lifetime by 3–13% in last node death (LND) compared to SBOA.
- ESBOA delivers more cumulative packets to the base station efficiently.

## Abstract

Cluster Head (CH) selection is a crucial process in clustered Wireless Sensor Networks (WSNs) because it directly affects energy balance and network lifetime. However, CH selection is an NP-hard optimization problem, and many metaheuristic-based methods suffer from limited search diversity and premature convergence, leading to uneven energy dissipation. This paper formulates CH selection as a multi-criteria energy-aware optimization problem and proposes an Enhanced Secretary Bird Optimization Algorithm (ESBOA). The proposed ESBOA improves the original Secretary Bird Optimization Algorithm by integrating logistic chaotic map-based population initialization to enhance early-stage exploration and an iterative local search mechanism to strengthen solution refinement in later iterations. A multi-criteria fitness function considering residual energy, distance to the base station, and node degree explicitly guides the optimization toward energy-efficient clustering. The proposed method is implemented in a Python 3.11.9-based simulation framework using a first-order radio energy model and evaluated against standard SBOA, Crested Porcupine Optimization (CPO), and Dung Beetle Optimization (DBO). Simulation results demonstrate that ESBOA preserves more alive nodes, maintains higher residual energy, delivers more cumulative packets to the base station, and extends network lifetime, achieving approximately 3–13% improvement in last node death (LND) compared with the standard SBOA.