透视图(图形)
计算机科学
网络拥塞
计算机网络
人工智能
网络数据包
作者
Inayat Ali,Seungwoo Hong,Pyungkoo Park,Tae Yeon Kim
标识
DOI:10.1145/3651863.3651885
摘要
Congestion in the network is a persistent issue that is becoming more challenging with the advent of technologies such as metaverse and immersive AR/VR applications. Therefore, we propose Enhanced ECN (EECN), a novel network-assisted congestion feedback protocol that redesigns the legacy ECN. EECN notifies two congestion levels encoded in the existing two ECN bits, unlike ECN which delivers only Boolean information about the congestion. Additionally, we propose a congestion control algorithm that leverages this multilevel congestion feedback from the network using EECN. Our proposed EECN feedback mechanism can coexist with the legacy ECN and requires minimal changes in the end hosts. Moreover, the proposed congestion control mechanism reduces packet drops by 74% compared to ECN with TCP New Reno and 96% compared to TCP New Reno without ECN. The marked packets are reduced by 30% compared to ECN. Furthermore, the proposed approach enhances the flow completion time of short-lived network flows.
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