Szczegóły publikacji
Opis bibliograficzny
Latency and energy-aware provisioning of network slices in cloud networks / Piotr BORYŁO, Massimo Tornatore, Piotr JAGLARZ, Nashid Shahriar, Piotr CHOŁDA, Raouf Boutaba // Computer Communications ; ISSN 0140-3664. — 2020 — vol. 157, s. 1–19. — Bibliogr. s. 18–19, Abstr. — Publikacja dostępna online od: 2020-04-04
Autorzy (6)
- AGHBoryło Piotr
- Tornatore Massimo
- AGHJaglarz Piotr
- Shahriar Nashid
- AGHChołda Piotr
- Boutaba Raouf
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 128324 |
|---|---|
| Data dodania do BaDAP | 2020-04-16 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.comcom.2020.03.050 |
| Rok publikacji | 2020 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Computer Communications |
Abstract
Modern network services are constantly increasing their requirements in terms of bandwidth, latency and cost efficiency. To satisfy these requirements, the concept of network slicing has been introduced in the context of next-generation 5G networks. However, to successfully provision resources to slices, a complex optimization problem must be addressed to allocate resources over a cloud network, i.e., a distributed computing infrastructure interconnected through high-capacity network links. In this study, we propose two new latency and energy-aware optimization models for provisioning 5G slices in cloud networks comprising both distributed computing and network resources. The proposed approaches differ from other existing solutions since we conduct our studies with respect to the end-to-end latency. Relevant models of latency and energy consumption are proposed based on a comprehensive review of the state-of-the-art. To effectively solve those optimization problems, a configurable heuristic is also proposed and investigated over different network topologies. Performance of the proposed heuristic is compared against near-optimal solutions. Moreover, we assess the importance of matching between resource provisioning algorithms and architectural assumptions related to 5G network slices and a proper problem modeling. © 2020 The Authors
