Research papers in the scalability of RPL routing for IoT investigate how the Routing Protocol for Low-Power and Lossy Networks (RPL) performs when deployed in large-scale, heterogeneous, and resource-constrained IoT environments. Since IoT networks can involve thousands of interconnected devices with diverse traffic demands, scalability is a critical factor influencing reliability, latency, control overhead, memory usage, and energy consumption. Studies highlight that while RPL is efficient for small to medium-scale static deployments, its performance deteriorates in large-scale networks due to issues like increased routing overhead, long convergence times, high packet loss, and limited support for dynamic topologies. Research explores enhancements such as scalable Objective Functions (multi-metric and load-balancing OFs), adaptive trickle timers, multipath routing, and hierarchical clustering to reduce congestion and evenly distribute network load. Analytical and simulation-based evaluations in tools like Cooja, NS-2, and NS-3 examine RPL’s scalability under varying node densities, traffic intensities, and application scenarios, while real-world testbeds validate these insights in practical IoT deployments. Advanced works propose SDN-enabled RPL, fog/edge-assisted RPL, and AI-driven adaptive RPL variants to dynamically optimize routing decisions and resource allocation in large networks. Security-aware scalability research further emphasizes resilience against rank manipulation, sinkhole, and denial-of-service attacks, which can severely affect large-scale deployments. Application-oriented studies illustrate scalability challenges in smart cities, industrial IoT, precision agriculture, and vehicular IoT, where dense and dynamic node populations demand highly adaptive and lightweight routing. Collectively, this literature underscores that ensuring the scalability of RPL is essential for its adoption in next-generation IoT ecosystems, and ongoing research continues to propose hybrid, adaptive, and intelligent solutions to meet the requirements of ultra-large-scale IoT networks empowered by 5G, 6G, and beyond.