Fair Scheduling in IEEE 802.11ah Networks for Internet of Things Applications

Lakshmi, L. Rajya; Sikdar, Biplab

doi:10.1109/globecom38437.2019.9013453

Cited by 1 publication

(1 citation statement)

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“…They also used Bianchi’s model [ 29 ] to compute the network throughput and validated the model with their own simulator. Lakshmi and Sikdar [ 38 ] proposed a fair scheduling grouping scheme with different traffic patterns. Their proposal is to assign a weight to the groups according their amount of service, i.e., the amount of data the stations of the group generate per second.…”

Section: Related Workmentioning

confidence: 99%

An Analytical Model for the Aggregate Throughput of IEEE 802.11ah Networks under the Restricted Access Window Mechanism

Soares

Carvalho

2022

Sensors

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The IEEE 802.11ah is an amendment to the IEEE 802.11 standard to support the growth of the Internet of Things (IoT). One of its main novelties is the restricted access window (RAW), which is a channel access feature designed to reduce channel contention by dividing stations into RAW groups. Each RAW group is further divided into RAW slots, and stations only attempt channel access during the RAW slot they were assigned to. In this paper, we propose a discrete-time Markov chain model to evaluate the average aggregate throughput of IEEE 802.11ah networks using the RAW mechanism under saturated traffic and ideal channel conditions. The proposed analytical model describes the behavior of an active station within its assigned RAW slot. A key aspect of the model is the consideration of the event of RAW slot time completion during a station’s backoff operation. We study the average aggregate network throughput for various numbers of RAW slots and stations in the network. The numerical results derived from our analytical model are compared to computer simulations based on an IEEE 802.11ah model developed for the ns-3 simulator by other researchers, and its performance is also compared to two other analytical models proposed in the literature. The presented results indicate that the proposed analytical model reaches the closest agreement with independently-derived computer simulations.

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Section: Related Workmentioning

confidence: 99%