Slicing in WiFi Networks Through Airtime-Based Resource Allocation

Abstract

Network slicing is one of the key enabling technologies for 5G networks. It allows infrastructure owners to assign resources to service providers (tenants), which will afterwards use them to satisfy their end-user demands. This paradigm, which changes the way networks have been traditionally managed, was initially proposed in the wired realm (core networks). More recently, the scientific community has paid attention to the integration of network slicing in wireless cellular technologies (LTE). However, there are not many works addressing the challenges that appear when trying to exploit slicing techniques over WiFi networks, in spite of their growing relevance. In this paper we propose a novel method of proportionally distributing resources in WiFi networks, by means of the airtime. We develop an analytical model, which shed light on how such resources could be split. The validity of the proposed model is assessed by means of simulation-based evaluation over the ns-3 framework.

Cloud Network Slicing: A systematic mapping study from scientific publications

“…However, we advocate that defining pricing strategies is a key factor for service adherence. In Figure 13, the Pricing Models were classified in Fixed (0,25%), Dynamic We conjecture that a mixed pricing approach, such as the one used by Amazon [7] , is more appropriate in the context of CNS, as the tenant would have more options for choosing. In addition, CNS providers would have more flexibility to negotiate with resource providers in order to form the end-to-end slice.…”

“…Although there is no unified definition on the concept of slice, a myriad of articles have been published in recent years in this area [7,8,9,10]. In the field of computer networks, slice takes advantage of technologies like SDN (Software Defined Networking) and NFV (Network Functions Virtualization), allowing to build a programmable and dynamic structure on demand.…”

Guaranteed Bit Rate Slicing in WiFi Networks

“…Therefore, to be able to implement our proposal of scheduling on a WiFi node we need to simulate the time slots. Our proposal is to use the idea of time quantums and the Adaptive Time-Excess Round Robin (ATERR) algorithm, which we proposed in our previous work [13]. The idea is that each time the scheduling algorithm assigns a transmission opportunity to a client, as much data as possible is transmitted to that client for the duration of a time quantum.…”

“…Even more, to implement the proposed scheduler, a queue per client and per slice is needed. This has already been proposed in our previous work [13] where we designed, analyzed, and implemented the necessary queuing structure.…”

“…In addition, we avoid traffic shaping, which can lead to inefficiencies if not controlled adequately. Furthermore, we use the queuing model proposed in our previous work [13], which contemplates the particularities of the hardware behaviour so as to avoid queue buildup at lower layers and to allow packet aggregation.…”