SDN-based Slice Orchestration and MAC Management for QoS delivery in IEEE 802.11 Networks

Isolani, Pedro Heleno; Cardona, Nelson; Donato, Carlos; Marquez-Barja, Johann M.; Granville, Lisandro Zambenedetti; Latré, Steven

doi:10.1109/sds.2019.8768642

Cited by 21 publications

(25 citation statements)

References 18 publications

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“…WTPs is deployed in the WiFi access points where the clients connect, and the network bandwidth is monitored and managed. For the more in-depth research on the functioning of 5G-EmPOWER, see [6,8].…”

Section: Slicing Enablersmentioning

confidence: 99%

Enabling QoS-secured Enhanced Non-Public Network Slices for Health Environments

Resende

Gonçalves

Both

et al. 2020

Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good

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5G networks are envisioned to provide high Quality of Service (QoS) for several use cases that differ on their network requirements and where they should be deployed. Some use cases are deployed in Public Land Mobile Network (PLMN) infrastructures that are managed by mobile network operators. However, for other use cases, devices connect to the services over private networks or Non-Public Network (NPN). The NPN deployment is mostly envisioned by companies that will benefit from Industry 4.0 and also eHealth to enhance QoS and network security. Network slicing is the 5G concept that comes to address the different service requirements over the same network. In this paper, we present an experimental study on deploying a network slicing solution for an NPN in health environments. This solution aims to provide both performance isolation over WiFi networks and privacy isolating the service traffic over the NPN network backhaul on the way to the application server, thus providing data confidentiality. CCS CONCEPTS • Networks → Network reliability.

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Section: Slicing Enablersmentioning

confidence: 99%

Enabling QoS-secured Enhanced Non-Public Network Slices for Health Environments

Resende

Gonçalves

Both

et al. 2020

Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good

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“…These approaches calculate bandwidth and latency indicators. It is worth mentioning that, when considering latency indicators, SMM is deployed, since latency tends to suer from the masking eect in the presence of outliers [19]. Besides, approaches based on Weihgted Moving Average (WMA) are also used to assign a greater weighting to the most recent data samples, whereas distant past samples have their weight vanished.…”

Section: Gómez Et Al Propose To Consider the Average Signal Strengthmentioning

confidence: 99%

“…Another proposal to deal with the challenges of monitoring large-scale wireless networks is to slice the network on a per-service basis [19,128,129]. Hence, the network slices take dierent forms depending on each service in question.…”

Section: Runtimementioning

confidence: 99%

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A Survey on Data Analysis on Large-Scale Wireless Networks: Online Stream Processing, Trends, and Challenges

Medeiros

Neto

Lopez

et al. 2020

Preprint

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In this paper we focus on knowledge extraction from large-scale wireless networks through stream processing. We present the primary methods for sampling, data collection, and monitoring of wireless networks and we characterize knowledge extraction as a machine learning problem on big data stream processing. We show the main trends in big data stream processing frameworks. Additionally, we explore the data preprocessing, feature engineering, and the machine learning algorithms applied to the scenario of wireless network analytics. We address challenges and present research projects in wireless network monitoring and stream processing. Finally, future perspectives, such as deep learning and reinforcement learning in stream processing, are anticipated.

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“…Therefore, SDN-tailored systems are envisioned to ease the creation of logical and isolated networks via slice abstractions [4]. In this context, E2E latency, accessibility, and throughput requirements have to be addressed simultaneously [5]. Therefore, in this paper, we present an SDN-based framework for slice orchestration using INT monitoring techniques.…”

Section: Introductionmentioning

confidence: 99%

An SDN-based Framework for Slice Orchestration using In-Band Network Telemetry in IEEE 802.11

Isolani

Haxhibeqiri

Moerman

et al. 2020

2020 6th IEEE Conference on Network Softwarization (NetSoft)

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The fifth generation of mobile networks (5G) and the Software-Defined Radio Access Networks (SD-RAN) architecture envision to support lower latency, enhanced reliability, massive connectivity, and improved energy efficiency. In this context, low latency is considered crucial and Ultra-Reliable Low Latency Communication (URLLC) as one of the key enablers. Currently, IEEE 802.11 networks cannot be programmed fine-grained enough nor manage multiple networks at runtime. Besides, in such scenarios, the coarse-grained level of monitoring information has been hindering troubleshooting and management. In this paper, we present an SDN-based framework where fine-grained End-to-End (E2E) network statistics can be gathered using Inband Network Telemetry (INT) and used for network control and management. With such fine-grained network information, we show how our system can enhance the Quality of Service (QoS) delivery through slice orchestration in IEEE 802.11 Radio Access Networks (RANs).

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SDN-based Slice Orchestration and MAC Management for QoS delivery in IEEE 802.11 Networks

Cited by 21 publications

References 18 publications

Enabling QoS-secured Enhanced Non-Public Network Slices for Health Environments

Enabling QoS-secured Enhanced Non-Public Network Slices for Health Environments

A Survey on Data Analysis on Large-Scale Wireless Networks: Online Stream Processing, Trends, and Challenges

An SDN-based Framework for Slice Orchestration using In-Band Network Telemetry in IEEE 802.11

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