A Designed Edge Storage System Based on SDN and UAV Assistance in Disaster Scenarios

Traditional edge distributed storage systems often suffer from cumbersome network configuration and high operational overhead for measuring network state information. During peak demand periods for data storage and retrieval by terminal devices, network links can become overloaded, adversely affecting data transmission performance. Furthermore, existing distributed storage systems typically consider only the remaining storage space of nodes when selecting storage nodes, neglecting the impact of network state and node load on system storage performance. To address these issues, this paper designs and implements an edge-distributed storage system assisted by software-defined network (SDN) and drones. The system uses SDN technology to measure network state, node load, and storage node load information. Drones fly above heavily loaded network nodes to offload traffic and balance the load across different links. For the selection of heavily loaded network nodes and storage nodes, this paper proposes a node selection algorithm based on a multiattribute decision model that comprehensively considers network state and node load. The algorithm identifies heavily loaded network nodes and suitable storage nodes, and the deployment of drones helps achieve traffic offloading and load balancing. Experimental tests on a wireless Mesh network topology demonstrate that the proposed wireless edge-distributed storage system outperforms existing edge-distributed storage systems in terms of storage performance. The proposed system significantly reduces storage time and maintains good performance even under increased traffic load, demonstrating excellent load-balancing capabilities.