Analysis of Bulk Data Collection in Wireless Sensor Networks Based on Random Scheduling

To facilitate the reliable and efficient transmission of large-scale data in Wireless Sensor Networks (WSN), this paper analyses the relationship between throughput and tree topology for the bulk data many-to-one collection mode with random scheduling. In addition, it designs a bulk data collection protocol based on random scheduling to verify the theoretical analysis. The protocol employs multi-channel dynamic allocation to avoid interferences, bulk data transmission for compressing control messages, and a block checking mechanism to enhance reliability. Theory and simulation demonstrate that, under the assumption of equal node data volume, interference-free multi-channel communication, fixed single node bulk data sending and receiving time, and negligible channel contention delay, the network collection time is predominantly influenced by the difference between the first and second largest subtree nodes in the topology. The experimental simulation data indicate that in a 25 -node tree topology, the subtree balanced structure enhances throughput by 29.17% and reduces collection time by approximately 23% compared to the unbalanced structure. The study provides an efficient and reliable solution for WSN bulk data transmission and reveals the key role of subtree equalization for network performance optimization.