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Most industrial applications demand determinism in terms of latency, reliability, and throughput. This goes hand in hand with the increased complexity of real-time network programability possibilities. To ensure network performance low-overhead, high-granularity, and timely network verification techniques need to be deployed. The first cornerstone of network verification ability is to enable end-to-end network monitoring, including end devices too. To achieve this, this article shows a novel and low overhead in-band network telemetry and monitoring technique for wireless networks focusing on IEEE 802.11 networks. A design of in-band network telemetry enabled node architecture is proposed and its proof of concept implementation is realized. The PoC realization is used to monitor a real-life SDN-based wireless network, enabling onthe-fly (re)configuration capabilities based on monitoring data. In addition, the proposed monitoring technique is validated in terms of monitoring accuracy, monitoring overhead, and network (re)configuration accuracy. It is shown that the proposed inband monitoring technique has 6 times lower overhead than other active monitoring techniques on a single-hop link. Besides this, it is demonstrated that (re)configuration decisions taken based on monitored data fulfill targeted application requirements, validating the suitability of the proposed monitoring technique.

In this letter, we propose an airtime-based Resource Allocation (RA) model for network slicing in IEEE 802.11 Radio Access Networks (RANs). We formulate this problem as a Quadratically Constrained Quadratic Program (QCQP), where the overall queueing delay of the system is minimized while strict Ultra-Reliable Low Latency Communication (URLLC) constraints are respected. We evaluated our model using three different solvers where the optimal and feasible sets of airtime configurations were computed. We also validated our model with experimentation in real hardware. Our results show that the solution time for computing optimal and feasible configurations vary according to the slice's demand distribution and the number of slices to be allocated. Our findings support the need for precise RA over IEEE 802.11 RANs and present the limitations of performing such optimizations at runtime.

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Abstract. Network Functions Virtualization (NFV) is an emerging initiative where virtualization is used to consolidate Network Functions (NFs) onto high volume servers (HVS), switches, and storage. In addition, NFV provides flexibility as Virtual Network Functions (VNFs) can be moved to different locations in the network. One of the major challenges of NFV is the allocation of demanded network services in the network infrastructures, commonly referred to as the Network Functions Virtualization -Resource Allocation (NFV-RA) problem. NFV-RA is divided into three stages: (i) Service Function Chain (SFC) composition, (ii) SFC embedding and (iii) SFC scheduling. Up to now, existing NFV-RA approaches have mostly tackled the SFC embedding stage taking the SFC composition as an assumption. Few approaches have faced the composition of the SFCs using heuristic approaches that do not guarantee optimal solutions. In this paper, we solve the first stage of the problem by characterizing the service requests in terms of NFs and optimally building the SFC using an Integer Linear Programming (ILP) approach.

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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