Refined Adaptive RED in TCP/IP Networks
Taehoon Kim, Kee-hyun Lee
Abstract
Taehoon Kim, Kee-hyun Lee
Abstract
Active queue management (AQM) refers to a family of packet dropping mechanisms for router queues that has been proposed to support end-to-end congestion control mechanisms in the Internet. The proposed AQM algorithm by the IETF is random early detection (RED). The RED algorithm allows network operators simultaneously to achieve high throughput and low average delay. However, the resulting average queue length is quite sensitive to the level of congestion. In this paper, we propose the refined adaptive RED (RARED), as a solution for reducing the sensitivity to parameters that affect RED performance. Based on simulations, we observe that the RARED scheme improves overall performance of the network. In particular, the RARED scheme reduces packet drop rate and improves goodput
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Active queue management (AQM) refers to a family of packet dropping mechanisms for router queues that has been proposed to support end-to-end congestion control mechanisms in the Internet. The proposed AQM algorithm by the IETF is random early detection (RED). The RED algorithm allows network operators simultaneously to achieve high throughput and low average delay. However, the resulting average queue length is quite sensitive to the level of congestion. In this paper, we propose the refined adaptive RED (RARED), as a solution for reducing the sensitivity to parameters that affect RED performance. Based on simulations, we observe that the RARED scheme improves overall performance of the network. In particular, the RARED scheme reduces packet drop rate and improves goodput
Key concepts: Random early detection, Goodput, Active queue management, Computer science, Computer network, Network congestion, Network packet, Queue