This project focuses on optimizing the layout of wireless sensor networks (WSNs) using the Honey Bee Colony Optimization (HBCO) algorithm. The primary objective is to find an optimal sensor placement that minimizes energy consumption, maximizes coverage, and enhances the efficiency of the WSN.
The proposed method leverages the behavior of bees to find the optimal locations for sensor nodes. Bees are deployed to explore the search space and communicate the most promising locations. This approach balances exploration and exploitation of the solution space, ultimately leading to an efficient layout for the WSN.
For a comprehensive evaluation, this project includes the implementation and comparison of various optimization algorithms, including:
- Binary Ant Colony Optimization (BA)
- Improved Harmony Search (iHS)
- Binary Biogeography-Based Optimization (bbO)
- Harmony Search (HS)
- Genetic Algorithm (GA)
These algorithms are implemented in MATLAB and compared against the HBCO-based layout optimization. The comparative analysis will help identify the strengths and weaknesses of each algorithm, allowing for a better understanding of their performance in the context of WSN layout optimization.
- Ensure you have MATLAB installed on your system.
- Download the project files from this repository.
- Open MATLAB and navigate to the project directory.
- Run the respective MATLAB scripts for each optimization algorithm to observe and compare the results.
Contributions to this project are welcome! If you have any suggestions, improvements, or additional algorithms to include in the comparative analysis, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.
Note: This readme file provides an overview of the project. For detailed information and code implementations, please refer to the project files.