Paxos Made Switch-y
November 16, 2015 Β· Declared Dead Β· π CCRV
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Huynh Tu Dang, Marco Canini, Fernando Pedone, Robert SoulΓ©
arXiv ID
1511.04985
Category
cs.DC: Distributed Computing
Cross-listed
cs.NI
Citations
122
Venue
CCRV
Last Checked
4 months ago
Abstract
This paper describes an implementation of the well-known consensus protocol, Paxos, in the P4 programming language. P4 is a language for programming the behavior of network forwarding devices (i.e., the network data plane). Moving consensus logic into network devices could significantly improve the performance of the core infrastructure and services in data centers. Moreover, implementing Paxos in P4 provides a critical use case and set of requirements for data plane language designers. In the long term, we imagine that consensus could someday be offered as a network service, just as point-to-point communication is provided today.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Distributed Computing
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Reproducing GW150914: the first observation of gravitational waves from a binary black hole merger
R.I.P.
π»
Ghosted
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
R.I.P.
π»
Ghosted
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
R.I.P.
π»
Ghosted
Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing
R.I.P.
π»
Ghosted
iFogSim: A Toolkit for Modeling and Simulation of Resource Management Techniques in Internet of Things, Edge and Fog Computing Environments
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted