2021
DOI: 10.1016/j.comnet.2021.108193
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Sphinx: A transport protocol for high-speed and lossy mobile networks

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Cited by 4 publications
(3 citation statements)
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“…In [Shi et al 2009], to tackle the same problem, it is presented RACC (Receiver Assistant Congestion Control mechanism), a TCP congestion control mechanism that combines loss-based and delay-based features. [Li et al 2021] proposes Sphinx, a novel transport protocol alternative to TCP that addresses the problem of throughput performance in mobile High Speed Lossy Networks, i.e., mobility is also taken into consideration. In a sense, we consider that our work is complementary to such efforts because regardless of the scheme employed in the Transport Layer, the chosen routes will allow higher throughput to the individual TCP sub-flows (e.g., for DVPTCP, with TCPBP, a lower number of subflows may be sufficient to obtain the same throughput of DVPTCP with routes computed with traditional metrics).…”
Section: Tcp-based Solutionsmentioning
confidence: 99%
“…In [Shi et al 2009], to tackle the same problem, it is presented RACC (Receiver Assistant Congestion Control mechanism), a TCP congestion control mechanism that combines loss-based and delay-based features. [Li et al 2021] proposes Sphinx, a novel transport protocol alternative to TCP that addresses the problem of throughput performance in mobile High Speed Lossy Networks, i.e., mobility is also taken into consideration. In a sense, we consider that our work is complementary to such efforts because regardless of the scheme employed in the Transport Layer, the chosen routes will allow higher throughput to the individual TCP sub-flows (e.g., for DVPTCP, with TCPBP, a lower number of subflows may be sufficient to obtain the same throughput of DVPTCP with routes computed with traditional metrics).…”
Section: Tcp-based Solutionsmentioning
confidence: 99%
“…There are several options for ingress controllers. We experiment with Nginx ingress controller 7 and Traefik ingress controller 8 , and opt for Traefik due to better performance. Kubeless leverages Kubernetes HPA for auto-scaling and does not support scaleto-zero.…”
Section: ) Kubelessmentioning
confidence: 99%
“…Nuclio, being relatively more CPU hungry, is able to scale more rapidly (in 40s) than Knative and OpenFaaS. For Kubeless, the fork-per-request and no queuing of function pods result in high latency and packet loss, which in turn contributes to lower throughput and lower CPU utilization [7]. Thus it leads to poor auto-scaling performance.…”
Section: Auto-scalingmentioning
confidence: 99%