Wireless Sensor Networks (WSNs) constitute a key enabling technology for the Internet of Things (IoT), providing large-scale, low-power sensing and monitoring capabilities in smart cities, industrial automation, environmental surveillance, healthcare, and agriculture. However, the integration of WSNs into the IoT framework exacerbates classical routing challenges such as energy scarcity, dynamic topology, data redundancy, link unreliability, and Quality of Service (QoS) constraints. At the same time, recent advances in optimization and artificial intelligence have introduced new opportunities for adaptive, context-aware, and cross-layer routing solutions. This paper presents a comprehensive review of routing optimization and challenges in WSNs under the IoT framework. First, we discuss the fundamental characteristics of WSNs in IoT scenarios and the design requirements of routing protocols. Then, we classify routing challenges into energy efficiency, scalability, reliability, latency, heterogeneity, mobility, and security-privacy issues. We examine state-of-the-art routing protocols and optimization approaches including ant colony optimization (ACO), particle swarm optimization (PSO), genetic algorithms (GA), fuzzy logic, mathematical programming, reinforcement learning (RL), and deep learning-based schemes. Special emphasis is placed on context-aware routing, software-defined networking (SDN)-enabled IoT, edge/fog-assisted routing, and blockchain-based secure routing. We also summarize and compare representative protocols and recent solutions published from 2020 to 2025 in terms of their design goals, performance metrics, and application domains. Finally, we identify open research problems and future directions towards self-optimizing, sustainable, and trustworthy routing mechanisms for next-generation IoT-driven WSNs.
Farahani et al. (2025) studied this question.