Enhancing Wireless Sensor Networks Features Using Software-Defined Networking Techniques and ACO Algorithms

Abstract

 Wireless sensor networks (WSNs) are the most important networks for things such as monitoring
natural phenomena, agriculture, health care, and so on. There are several challenges associated with using WSNs,
the most important of which are energy consumption, expansion issues, or even data routing issues. There are many
techniques and algorithms that can address these challenges and make it easier to use WSNs. These techniques and
algorithms vary depending on the challenge to be overcome. In this study, Software Defined Network (SDN)
technology was used for the purpose of improving WSNs and saving energy for nodes in those networks. The Ant
Colony Optimization (ACO) algorithm, which is an algorithm that follows ants’ foraging method, was also used.
This algorithm was used to find the shortest data path from the starting node to the target node. The results of the
proposed system was a significant improvement in the performance of WSNs. The system saved energy, removed
dead nodes, and found better and shorter paths to reach the target nodes. The proposed approach was versatile and
adaptable, making it suitable for various WSN applications and deployment scenarios. The results of the proposed
system led to energy savings of up to 0.891 mj and only 35 nodes compared to traditional methods, which can have
up to 74 dead nodes.