Efficient load-balancing mechanisms are critical for maximizing performance and increasing the quality of service (QoS) of data center networks (DCNs). Obtaining the optimal QoS while minimizing resource consumption remains a significant challenge. This paper proposes the streamlined pathway (SP) model, which is a flow scheduling solution that requires minimal statistical knowledge of the DCN data plane. The SP model utilizes the software-defined networks (SDNs) paradigm with less information gathered from the DCN data plane besides the traditional hash-based flow scheduling mechanism, the Equal-Cost Multi-Path (ECMP). In SDN, the proposed methodology harnesses a minimal, yet powerful set of statistical data extracted from the DCN data plane, including port throughput and elephant flow information on the aggregate switches of the DCN fat-tree topology. Several experiments in addition to theoretical analysis have been conducted to demonstrate the efficiency of the proposed SP model in terms of QoS enhancement. These results confirm that SP outperforms leading techniques such as Sieve, Hedera, and ECMP, concerning bisection bandwidth, DCN link utilization, packet loss, and packet delivery latency.