A survey on observability of distributed edge & container-based microservices
Edge computing is proposed as a technical enabler for meeting emerging network
technologies (such as 5G and Industrial Internet of Things), stringent application …
technologies (such as 5G and Industrial Internet of Things), stringent application …
Rethinking data-driven networking with foundation models: challenges and opportunities
Foundational models have caused a paradigm shift in the way artificial intelligence (AI)
systems are built. They have had a major impact in natural language processing (NLP), and …
systems are built. They have had a major impact in natural language processing (NLP), and …
Digital twin for networking: A data-driven performance modeling perspective
Emerging technologies and applications make the network unprecedentedly complex and
heterogeneous, leading the network operations to be costly and risky. The digital twin …
heterogeneous, leading the network operations to be costly and risky. The digital twin …
RouteNet-Fermi: Network modeling with graph neural networks
M Ferriol-Galmés, J Paillisse… - … ACM transactions on …, 2023 - ieeexplore.ieee.org
Network models are an essential block of modern networks. For example, they are widely
used in network planning and optimization. However, as networks increase in scale and …
used in network planning and optimization. However, as networks increase in scale and …
Dons: Fast and affordable discrete event network simulation with automatic parallelization
Discrete Event Simulation (DES) is an essential tool for network practitioners. Unfortunately,
existing DES simulators cannot achieve satisfactory performance at the scale of modern …
existing DES simulators cannot achieve satisfactory performance at the scale of modern …
Deepqueuenet: Towards scalable and generalized network performance estimation with packet-level visibility
Network simulators are an essential tool for network operators, and can assist important
tasks such as capacity planning, topology design, and parameter tuning. Popular simulators …
tasks such as capacity planning, topology design, and parameter tuning. Popular simulators …
[HTML][HTML] AIDA—A holistic AI-driven networking and processing framework for industrial IoT applications
Industry 4.0 is characterized by digitalized production facilities, where a large volume of
sensors collect a vast amount of data that is used to increase the sustainability of the …
sensors collect a vast amount of data that is used to increase the sustainability of the …
{CausalSim}: A Causal Framework for Unbiased {Trace-Driven} Simulation
We present CausalSim, a causal framework for unbiased trace-driven simulation. Current
trace-driven simulators assume that the interventions being simulated (eg, a new algorithm) …
trace-driven simulators assume that the interventions being simulated (eg, a new algorithm) …
m3: Accurate flow-level performance estimation using machine learning
Data center network operators often need accurate estimates of aggregate network
performance. Unfortunately, existing methods for estimating aggregate network statistics are …
performance. Unfortunately, existing methods for estimating aggregate network statistics are …
Network Traffic Prediction Model in a Data-Driven Digital Twin Network Architecture
The proliferation of immersive services, including virtual reality/augmented reality,
holographic content, and the metaverse, has led to an increase in the complexity of …
holographic content, and the metaverse, has led to an increase in the complexity of …