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pro vyhledávání: '"Parisis, George"'
Reinforcement Learning (RL) has gained significant momentum in the development of network protocols. However, RL-based protocols are still in their infancy, and substantial research is required to build deployable solutions. Developing a protocol bas
Externí odkaz:
http://arxiv.org/abs/2302.04519
Publikováno v:
In Computer Communications 1 October 2024 226-227
Autor:
Valentine, Aiden, Parisis, George
In this paper, we present our work in designing and implementing a LEO satellite constellation simulation model1 within OMNeT++ and INET, which is validated by comparing the results with existing work. Our model builds upon the fundamentals of the Op
Externí odkaz:
http://arxiv.org/abs/2109.12046
Software-defined networking (SDN) enables advanced operation and management of network deployments through (virtually) centralised, programmable controllers, which deploy network functionality by installing rules in the flow tables of network switche
Externí odkaz:
http://arxiv.org/abs/2008.06149
Publikováno v:
TNET.2021.3059542
Getting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an equally imp
Externí odkaz:
http://arxiv.org/abs/2007.10150
In software-defined networks (SDN), a controller program is in charge of deploying diverse network functionality across a large number of switches, but this comes at a great risk: deploying buggy controller code could result in network and service di
Externí odkaz:
http://arxiv.org/abs/2004.11988
Publikováno v:
IEEE/ACM Transactions on Networking 2021
In this paper we propose SCDP, a general-purpose data transport protocol for data centres that, in contrast to all other protocols proposed to date, supports efficient one-to-many and many-to-one communication, which is extremely common in modern dat
Externí odkaz:
http://arxiv.org/abs/1909.08928
Getting good statistical models of traffic on network links is a well-known, often-studied problem. A lot of attention has been given to correlation patterns and flow duration. The distribution of the amount of traffic per unit time is an equally imp
Externí odkaz:
http://arxiv.org/abs/1902.03853
Akademický článek
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Autor:
Messager, Antoine, Parisis, George, Kiss, Istvan Z, Harper, Robert, Tee, Phil, Berthouze, Luc
We consider the problem of inferring the functional connectivity of a large-scale computer network from sparse time series of events emitted by its nodes. We do so under the following three domain-specific constraints: (a) non-stationarity of the fun
Externí odkaz:
http://arxiv.org/abs/1802.04036