Published Paper Details:

Inspired by the collective behavior of natural systems, Swarm Intelligence (SI) has become a game-changing method for optimizing Internet of Things (IoT) networks. SI-based algorithms, like Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and the Firefly Algorithm (FA), are characterized by self-organization, decentralization, and adaptability. They provide scalable and effective solutions to challenging issues in Internet of Things environments. These consist of task scheduling and routing optimization., energy management, fault tolerance, and security. The absence of a central controller in SI systems enhances their robustness and scalability in large distributed networks. Moreover, the integration of block chain-based security mechanisms ensures tamper-proof and trustworthy frameworks for IoT systems. As IoT evolves, combining SI with cutting-edge technologies like 6G, edge computing, and autonomous systems promises to revolutionize applications in smart cities, Industry 4.0, healthcare, and intelligent transportation.