@Article{cmc.2024.056925,
AUTHOR = {Jinlin Xu, Wansu Pan, Haibo Tan, Longle Cheng, Xiaofeng Li},
TITLE = {An Adaptive Congestion Control Optimization Strategy in SDN-Based Data Centers},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {81},
YEAR = {2024},
NUMBER = {2},
PAGES = {2709--2726},
URL = {http://www.techscience.com/cmc/v81n2/58665},
ISSN = {1546-2226},
ABSTRACT = {The traffic within data centers exhibits bursts and unpredictable patterns. This rapid growth in network traffic has two consequences: it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load. Consequently, persistent overload situations eventually result in network congestion. The Software Defined Network (SDN) technology is employed in data centers as a network architecture to enhance performance. This paper introduces an adaptive congestion control strategy, named DA-DCTCP, for SDN-based Data Centers. It incorporates Explicit Congestion Notification (ECN) and Round-Trip Time (RTT) to establish congestion awareness and an ECN marking model. To mitigate incorrect congestion caused by abrupt flows, an appropriate ECN marking is selected based on the queue length and its growth slope, and the congestion window (CWND) is adjusted by calculating RTT. Simultaneously, the marking threshold for queue length is continuously adapted using the current queue length of the switch as a parameter to accommodate changes in data centers. The evaluation conducted through Mininet simulations demonstrates that DA-DCTCP yields advantages in terms of throughput, flow completion time (FCT), latency, and resistance against packet loss. These benefits contribute to reducing data center congestion, enhancing the stability of data transmission, and improving throughput.},
DOI = {10.32604/cmc.2024.056925}
}