Djamal Zeghlache

Hassan Fawaz, Julien Lesca, Pham Tran Anh Quang et al.

In this paper, we explore the use of multi-agent deep learning as well as learning to cooperate principles to meet stringent service level agreements, in terms of throughput and end-to-end delay, for a set of classified network flows. We consider agents built on top of a weighted fair queuing algorithm that continuously set weights for three flow groups: gold, silver, and bronze. We rely on a novel graph-convolution based, multi-agent reinforcement learning approach known as DGN. As benchmarks, we propose centralized and distributed deep Q-network approaches and evaluate their performances in different network, traffic, and routing scenarios, highlighting the effectiveness of our proposals and the importance of agent cooperation. We show that our DGN-based approach meets stringent throughput and delay requirements across all scenarios.

Erick Petersen, Jorge López, Natalia Kushik et al.

This paper presents the design and architecture of a network emulator whose links' parameters (such as delay and bandwidth) vary at different time instances. The emulator can thus be used in order to test and evaluate novel solutions for such networks, before their final deployment. To achieve this goal, different existing technologies are carefully combined to emulate link dynamicity, automatic traffic generation, and overall network device emulation. The emulator takes as an input a formal model of the network to emulate and configures all required software to execute live software instances of the desired network components, in the requested topology. We devote our study to the so-called dynamic link networks, with potentially asymmetric links. Since emulating asymmetric dynamic links is far from trivial (even with the existing state-of-the-art tools), we provide a detailed design architecture that allows this. As a case study, a satellite network emulation is presented. Experimental results show the precision of our dynamic assignments and the overall flexibility of the proposed solution.

Erick Petersen, Jorge López, Natalia Kushik et al.

A novel model-based approach to verify dynamic networks is proposed; the approach consists in formally describing the network topology and dynamic link parameters. A many sorted first order logic formula is constructed to check the model with respect to a set of properties. The network consistency is verified using an SMT-solver, and the formula is used for the run-time network verification when a given static network instance is implemented. The z3 solver is used for this purpose and corresponding preliminary experiments showcase the expressiveness and current limitations of the proposed approach.