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Communication Dans Un Congrès Année : 2020

Noisy neighbor detection and avoidance for network slicing in 5G

Résumé

This paper addresses the problem of noisy neighbor in the context of network slicing in 5G networks. Noisy neighbor is considered as an important issue since VNFs or VMs running on the same physical machine compete for resources, such as CPU, memory or bandwidth, which can degrade their performance. In this paper, we present a new approach based on supervised learning and optimization that detects and avoids bad neighboring VNFs through intelligent VNFs placement and migration.
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Dates et versions

hal-03511737 , version 1 (05-01-2022)

Identifiants

  • HAL Id : hal-03511737 , version 1

Citer

Hanane Biallach, Marouen Mechtri, Chaima Ghribi. Noisy neighbor detection and avoidance for network slicing in 5G. 17th IEEE Annual Consumer Communications & Networking Conference (CCNC 2020), Jan 2020, Las Vegas, United States. ⟨hal-03511737⟩
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