Zobrazeno 1 - 10
of 106
pro vyhledávání: '"Vanbever, Laurent"'
The proxy design pattern allows Ethereum smart contracts to be simultaneously immutable and upgradeable, in which an original contract is split into a proxy contract containing the data storage and a logic contract containing the implementation logic
Externí odkaz:
http://arxiv.org/abs/2409.13563
Learning precise distributions of traffic features (e.g., burst sizes, packet inter-arrival time) is still a largely unsolved problem despite being critical for management tasks such as capacity planning or anomaly detection. A key limitation nowaday
Externí odkaz:
http://arxiv.org/abs/2405.10931
Machine learning (ML) is a powerful tool to model the complexity of communication networks. As networks evolve, we cannot only train once and deploy. Retraining models, known as continual learning, is necessary. Yet, to date, there is no established
Externí odkaz:
http://arxiv.org/abs/2405.10290
Autor:
De Sensi, Daniele, Molero, Edgar Costa, Di Girolamo, Salvatore, Vanbever, Laurent, Hoefler, Torsten
The allreduce operation is an essential building block for many distributed applications, ranging from the training of deep learning models to scientific computing. In an allreduce operation, data from multiple hosts is aggregated together and then b
Externí odkaz:
http://arxiv.org/abs/2309.16214
Programmable packet scheduling allows the deployment of scheduling algorithms into existing switches without need for hardware redesign. Scheduling algorithms are programmed by tagging packets with ranks, indicating their desired priority. Programmab
Externí odkaz:
http://arxiv.org/abs/2308.00797
Autor:
Bühler, Tobias, Milolidakis, Alexandros, Jacob, Romain, Chiesa, Marco, Vissicchio, Stefano, Vanbever, Laurent
The lack of security of the Internet routing protocol (BGP) has allowed attackers to divert Internet traffic and consequently perpetrate service disruptions, monetary frauds, and even citizen surveillance for decades. State-of-the-art defenses rely o
Externí odkaz:
http://arxiv.org/abs/2301.12843
We present a new method for scaling automatic configuration of computer networks. The key idea is to relax the computationally hard search problem of finding a configuration that satisfies a given specification into an approximate objective amenable
Externí odkaz:
http://arxiv.org/abs/2211.01980
Generalizing machine learning (ML) models for network traffic dynamics tends to be considered a lost cause. Hence for every new task, we design new models and train them on model-specific datasets closely mimicking the deployment environments. Yet, a
Externí odkaz:
http://arxiv.org/abs/2207.05843
Today, network devices share buffer across priority queues to avoid drops during transient congestion. While cost-effective most of the time, this sharing can cause undesired interference among seemingly independent traffic. As a result, low-priority
Externí odkaz:
http://arxiv.org/abs/2105.10553
Autor:
De Sensi, Daniele, Costa Molero, Edgar, Di Girolamo, Salvatore, Vanbever, Laurent, Hoefler, Torsten
Publikováno v:
In Future Generation Computer Systems March 2024 152:70-82