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Published November 28, 2022 | Version v1
Journal article Open

IMPROVING QOS AND FAIRNESS OF PACKET SCHEDULING IN WIMAX NETWORKS

  • 1. Computer Networks Research Lab, Electrical Engineering Technologies Research Center, Sahand University of Technology, Tabriz, Iran.

Description

Abstract:

WiMAX (defined in IEEE 802.16) is a broadband wireless technology suitable for metropolitan area that has better efficiency and more scalability than wired networks. The WiMAX can be used for various applications such as Internet and multimedia (video streaming). Each of these applications has diverse quality of service (QoS) requirements to be satisfied. Scheduling problem in WiMAX networks is a vital challenging. To satisfy various necessities, a proper scheduling algorithm must be designed for WiMAX. Qualities of service and fairness criteria are known as the most important efficiency and evaluation factors. Therefore, we need an algorithm that meets both fairness and QoS. This paper provides two contributions. First, dynamic frame division is proposed for uplink and downlink channel in order to provide dynamic bandwidth allocation for uplink and downlink traffic, where fairness is divided between uplink and downlink channels. This division is based on the requested bandwidth for each class on each link and their coefficients. Simulation results show that when one of the links (either uplink or downlink traffic) requirements is less than half of the available bandwidth and another link demand is more than half of the bandwidth, the frame utilization of the proposed dynamic division is better than static bandwidth allocation [1]. Meanwhile, the dynamic bandwidth allocation approach always has better loss and delay performances than the static bandwidth allocation. Second, the QoS and fairness (QAF) scheduling algorithm is proposed, which is based on the EDF + WFQ + FIFO algorithm. In this way, bandwidth is allocated to each subscriber station (SS) based on its traffic priorities and the weights of its traffic classes. The QAF improves loss, delay, and fairness compared with the EDF algorithm.

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