| 1. |
- Diaz Zayas, Almudena, et al.
(författare)
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A Modular Experimentation Methodology for 5G Deployments : The 5GENESIS Approach
- 2020
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 20:22
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Tidskriftsartikel (refereegranskat)abstract
- The high heterogeneity of 5G use cases requires the extension of the traditional per-component testing procedures provided by certification organizations, in order to devise and incorporate methodologies that cover the testing requirements from vertical applications and services. In this paper, we introduce an experimentation methodology that is defined in the context of the 5GENESIS project, which aims at enabling both the testing of network components and validation of E2E KPIs. The most important contributions of this methodology are its modularity and flexibility, as well as the open-source software that was developed for its application, which enable lightweight adoption of the methodology in any 5G testbed. We also demonstrate how the methodology can be used, by executing and analyzing different experiments in a 5G Non-Standalone (NSA) deployment at the University of Malaga. The key findings of the paper are an initial 5G performance assessment and KPI analysis and the detection of under-performance issues at the application level. Those findings highlight the need for reliable testing and validation procedures towards a fair benchmarking of generic 5G services and applications.
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| 2. |
- Emmelmann, Marc, et al.
(författare)
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Deliverable 6.2: Trials and experimentation (cycle 2)
- 2020
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Rapport (refereegranskat)abstract
- This deliverable presents the second cycle of trials and experimentation activities executed over 5GENESIS facilities. The document is the continuation of deliverable D6.1, in the sense that it captures tests carried out over the evolved infrastructures hosting 5GENESIS facilities following the methodology defined in D6.1. In this document 8 main KPIs and 4 application specific validation trials achieved, under 123 experiments that performed in total. The tests focus more on i) the evolved 5G infrastructure deployments that includes radio and core elements in non-standalone (NSA) deployment configurations based on commercial and open implementations, and ii) the use of Open 5GENESIS Suite for the execution of the tests.
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| 3. |
- Kousias, Konstantinos, et al.
(författare)
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Coverage and Deployment Analysis of Narrowband Internet of Things in the Wild
- 2020
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Ingår i: IEEE Communications Magazine. - : Institute of Electrical and Electronics Engineers (IEEE). - 0163-6804 .- 1558-1896. ; 58:9, s. 39-45
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Tidskriftsartikel (refereegranskat)abstract
- Narrowband Internet of Things (NB-IoT) is gaining momentum as a promising technology for massive machine type communication. Given that its deployment is rapidly progressing worldwide, measurement campaigns and performance analyses are needed to better understand the system and move toward its enhancement. With this aim, this article presents a large-scale measurement campaign and empirical analysis of NB-IoT on operational networks, and discloses valuable insights in terms of deployment strategies and radio coverage performance. The reported results also serve as examples showing the potential usage of the collected dataset, which we make open source along with a lightweight data visualization platform.
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| 4. |
- Wu, Hongjia, et al.
(författare)
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Peekaboo : Learning-Based Multipath Scheduling for Dynamic Heterogeneous Environments
- 2020
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Ingår i: IEEE Journal on Selected Areas in Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0733-8716 .- 1558-0008. ; 38:10, s. 2295-2310
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Tidskriftsartikel (refereegranskat)abstract
- Multipath transport protocols utilize multiple network paths (e.g., WiFi and cellular) to achieve improved performance and reliability, compared with their single-path counterparts. The scheduler of a multipath transport protocol determines how to distribute the data packets onto different paths. However, state-of-the-art multipath schedulers face the challenge when dealing with heterogeneous paths with dynamic path characteristics (i.e., packet loss, fluctuation of delay). In this paper, we propose Peekaboo, a novel learning-based multipath scheduler that is aware of the dynamic characteristics of the heterogeneous paths. Peekaboo is able to learn scheduling decisions to adopt over time based on the current path characteristics and dynamicity levels - from both deterministic and stochastic perspectives. We implement Peekaboo in Multipath QUIC (MPQUIC) and compare it with state-of-the-art multipath schedulers for a wide range of dynamic heterogeneous environments, upon both emulated and real networks. Our results show that Peekaboo outperforms the other schedulers by up to 31.2% in emulated networks and up to 36.3% in real network scenarios.
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