Pierre Sens
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View article: IRENE: a fluId layeR finitE-elemeNt softwarE
IRENE: a fluId layeR finitE-elemeNt softwarE Open
We present a finite-element software library, IRENE, which allows to solve numerically the dynamics of a viscous fluid layer embedded in three-dimensional space. Unlike finite-element libraries present in the literature, IRENE can handle t…
View article: Network Slice Monitoring System For Disaster Detection
Network Slice Monitoring System For Disaster Detection Open
The use of monitoring systems for risk areas has increased significantly, especially with the use of IoT applications, which has driven Early Warning Systems (EWS). However, risk situations due to natural disasters can cause malfunction of…
View article: OMAHA: Opportunistic Message Aggregation for pHase-based Algorithms
OMAHA: Opportunistic Message Aggregation for pHase-based Algorithms Open
In the cloud computing context, several applications run concurrently over the same underlying physical infrastructure. Phase-based algorithms are key building blocks for many distributed applications such as DBMS or transaction validation…
View article: A distributed convergecast algorithm for dynamic mobile networks
A distributed convergecast algorithm for dynamic mobile networks Open
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View article: OMAHA: Opportunistic Message Aggregation for pHase-based Algorithms
OMAHA: Opportunistic Message Aggregation for pHase-based Algorithms Open
International audience
View article: Multi-FedLS: a Framework for Cross-Silo Federated Learning Applications on Multi-Cloud Environments
Multi-FedLS: a Framework for Cross-Silo Federated Learning Applications on Multi-Cloud Environments Open
Federated Learning (FL) is a distributed Machine Learning (ML) technique that can benefit from cloud environments while preserving data privacy. We propose Multi-FedLS, a framework that manages multi-cloud resources, reducing execution tim…
View article: SeMaFoR - Self-Management of Fog Resources with Collaborative Decentralized Controllers
SeMaFoR - Self-Management of Fog Resources with Collaborative Decentralized Controllers Open
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View article: Alternating MPR: a balanced broadcast algorithm for MANETs
Alternating MPR: a balanced broadcast algorithm for MANETs Open
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View article: Optimizing Execution Time and Costs of Cross-Silo Federated Learning Applications with Datasets on different Cloud Providers
Optimizing Execution Time and Costs of Cross-Silo Federated Learning Applications with Datasets on different Cloud Providers Open
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View article: Towards a Federated Learning Framework on a Multi-Cloud Environment
Towards a Federated Learning Framework on a Multi-Cloud Environment Open
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View article: A predictive approach for dynamic replication of operators in distributed stream processing systems
A predictive approach for dynamic replication of operators in distributed stream processing systems Open
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View article: A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement
A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement Open
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View article: Evaluating Federated Learning Scenarios in a Tumor Classification Application
Evaluating Federated Learning Scenarios in a Tumor Classification Application Open
Federated Learning is a new area of distributed Machine Learning (ML) that emerged to deal with data privacy concerns. In this approach, each client has access to a local and private dataset. They only exchange the model weights and update…
View article: A Multi-Metric Adaptive Stream Processing System
A Multi-Metric Adaptive Stream Processing System Open
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View article: Centrality-Based Eventual Leader Election in Dynamic Networks
Centrality-Based Eventual Leader Election in Dynamic Networks Open
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View article: Scheduling Bag-of-Tasks in Clouds Using Spot and Burstable Virtual Machines
Scheduling Bag-of-Tasks in Clouds Using Spot and Burstable Virtual Machines Open
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View article: DRL-based Slice Placement Under Non-Stationary Conditions
DRL-based Slice Placement Under Non-Stationary Conditions Open
We consider online learning for optimal network slice placement under the assumption that slice requests arrive according to a non-stationary Poisson process. We propose a framework based on Deep Reinforcement Learning (DRL) combined with …
View article: DRL-based Slice Placement under Realistic Network Load Conditions
DRL-based Slice Placement under Realistic Network Load Conditions Open
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View article: DRL-based Slice Placement Under Non-Stationary Conditions
DRL-based Slice Placement Under Non-Stationary Conditions Open
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View article: DRL-based Slice Placement under Realistic Network Load Conditions
DRL-based Slice Placement under Realistic Network Load Conditions Open
We propose to demonstrate a network slice placement optimization solution based on Deep Reinforcement Learning (DRL), referred to as Heuristically-controlled DRL, which uses a heuristic to control the DRL algorithm convergence. The solutio…
View article: FIFO and Atomic broadcast algorithms with bounded message size for dynamic systems
FIFO and Atomic broadcast algorithms with bounded message size for dynamic systems Open
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View article: A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement
A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement Open
Network Slice placement with the problem of allocation of resources from a virtualized substrate network is an optimization problem which can be formulated as a multiobjective Integer Linear Programming (ILP) problem. However, to cope with…
View article: Topology Aware Leader Election Algorithm for Dynamic Networks
Topology Aware Leader Election Algorithm for Dynamic Networks Open
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View article: Scheduling Bag-of-Tasks in Clouds using Spot and Burstable Virtual Machines
Scheduling Bag-of-Tasks in Clouds using Spot and Burstable Virtual Machines Open
Leading Cloud providers offer several types of Virtual Machines (VMs) in diverse contract models, with different guarantees in terms of availability and reliability. Among them, the most popular contract models are the on-demand and the sp…
View article: Heuristic for Edge-enabled Network Slicing Optimization using the Power\n of Two Choices
Heuristic for Edge-enabled Network Slicing Optimization using the Power\n of Two Choices Open
We propose an online heuristic algorithm for the problem of network slice\nplacement optimization. The solution is adapted to support placement on large\nscale networks and integrates Edge-specific and URLLC constraints. We rely on\nan app…
View article: Edge-enabled Optimized Network Slicing in Large Scale Networks
Edge-enabled Optimized Network Slicing in Large Scale Networks Open
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