This thesis analyzes the performance of Quantized Congestion Notification (QCN) during data access from clustered servers in data centers. The reasons why QCN does not perform adequately in these situations are examined and several modifications are proposed to the protocol to improve its performance in these scenarios. The causes of QCN performance degradation are traced to flow rate variability, and it is shown that adaptive sampling at the switch and adaptive self-increase of flow rates at the QCN rate limiter significantly enhance QCN performance in a TCP Incast setup. The performance of QCN is compared against TCP modifications in a heterogeneous environment, and it is shown that modifications to QCN yield better performance. Finally, the performance of QCN with the proposed modifications is compared with that of unmodified QCN in other workloads to show that the modifications do not negatively affect QCN performance in general.