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Mu: An Efficient, Fair and Responsive Serverless Framework for Resource-Constrained Edge Clouds.

, , , , , , , , , and . SoCC, page 168-181. ACM, (2021)

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Flurries: Countless Fine-Grained NFs for Flexible Per-Flow Customization., , , , and . CoNEXT, page 3-17. ACM, (2016)LT-TCP: End-to-End Framework to Improve TCP Performance over Networks with Lossy Channels., , , and . IWQoS, volume 3552 of Lecture Notes in Computer Science, page 81-93. Springer, (2005)NetML: An NFV Platform with Efficient Support for Machine Learning Applications., and . NetSoft, page 396-404. IEEE, (2019)The workstation on the network: performance considerations for the communications interface., and . WWOS, page 105-108. (1989)DeepScaling: microservices autoscaling for stable CPU utilization in large scale cloud systems., , , , , , , , and . SoCC, page 16-30. ACM, (2022)D-LiTE: A platform for evaluating DASH performance over a simulated LTE network., , , , , and . LANMAN, page 1-2. IEEE, (2016)The Stability of a Flow Merge Point with Non-Interleaving Cut-Through Scheduling Disciplines., and . INFOCOM, page 1231-1238. IEEE Computer Society, (1999)Machine learning at the network edge for automated home intrusion monitoring., and . ICNP, page 1-6. IEEE Computer Society, (2017)Design Challenges for High Performance, Scalable NFV Interconnects., , , , and . KBNets@SIGCOMM, page 49-54. ACM, (2017)Protocol Specification Using Parameterized Communicating Extended Finite Stte Machines - A Case Study of The ATM ABR Rate Control Scheme., , , and . ICNP, page 208-217. IEEE Computer Society, (1996)