Adaptive Dynamic Bandwidth Allocation in Smart Cities Using Software-Defined Networking
Renaldy Fredyan, Luthfan Hadi Pramono, Khairunnisa Khairunnisa · Engineering Technology & Applied Science Research · 2025
The rapid expansion of smart city applications has led to an increased demand for real-time data processing and optimal resource utilization. However, traditional static bandwidth allocation techniques often fail to meet the changing needs of these services. This research aims to provide an alternative solution through adaptive dynamic bandwidth allocation based on Software-Defined Networking (SDN) to enhance bandwidth distribution in smart cities. The proposed system utilizes POX software to dynamically allocate bandwidth based on real-time network conditions and service requirements, leveraging SDN's programmability and central control capabilities. The system prioritizes network allocation according to device priority and bandwidth needs to improve overall network efficiency. The findings of the simulation demonstrate that adaptive dynamic bandwidth allocation using SDN significantly improves network performance compared to conventional static techniques, reducing latency and enhancing Quality of Service (QoS) for critical smart city applications, such as traffic control and public safety. This approach presents a promising alternative for future smart city network infrastructure.