A Comprehensive Review of Shortest Path Algorithms for Network Routing

The rapid development of digital technology and the increasing interconnection of devices have made computer networks indispensable to modern life. Global data movement, communication, and applications like cloud computing, IoT, e-commerce, and smart cities are all made possible by these networks. Routing algorithms particularly shortest path algorithms are crucial for determining the most effective data transmission routes and are largely responsible for the dependability and efficiency of these networks. Because these algorithms maintain stability and reliability while lowering latency, costs, and energy consumption, they are crucial to network operation.

Shortest path problem solving has long relied on fundamental algorithms with origins in graph theory, such as Bellman-Ford and Dijkstra's. Despite their successes, the growing complexity and dynamic nature of contemporary networks have exposed their shortcomings. Advanced approaches, including heuristic, hybrid, and AI-driven methods, have been developed to get around these challenges. Innovations like ant colony optimization and blockchain-based algorithms have improved computing efficiency, security, and adaptability.

The Internet of Things, VANETs, and SDNs are just a few of the domains that use these algorithms; each has specific requirements, like real-time adaptation and energy efficiency. Reinforcement learning and prediction models driven by machine learning have further increased routing efficiency, while simulation tools such as Mininet and OMNeT++ have been essential for evaluating algorithm performance in practical scenarios. As emerging technologies like blockchain and quantum computing become more widely accepted, shortest path algorithms will continue to advance, ensuring their suitability in the rapidly evolving digital environment. This study, which looks at their development, applications, and possible future directions, emphasizes their importance in creating modern networks.