Nawab, IramIramNawabKulkarni, Sameer G.Sameer G.Kulkarni2025-08-312025-08-312023-01-01[9798350302080]10.1109/CCGridW59191.2023.000832-s2.0-85166733800http://repository.iitgn.ac.in/handle/IITG2025/26974The cloud services made accessible over different network paths and served by multiple backend servers demand distributed rate-limiting solutions. Emerging technologies such as 5G/6G, IoT, and Edge cloud are changing the network landscape dynamically and demand more sophisticated rate-limiting policies. However, the current designs of Distributed rate limiters (DRLs) demand to tradeoff the overheads (communication, computation, state/memory) with accuracy in terms of configuring the rate-limiters with parameters like the number of connections, bandwidth, etc. Hence, we propose accurate and low-overhead containerized distributed rate-limiting functions managed by hierarchical software-defined networking controllers.falseDistributed Rate limiters | Edge cloud | Reinforcement learning | Software-defined networking (SDN) | virtualized network functions (VNF)Conference Paper354-35620230cpConference Proceeding0