This thesis proposes a Quality of Service (QoS) architecture for
IEEE 802.16, which includes a contention period management
algorithm and a price-based scheduling framework. We first derive
the optimal contention window size to properly manage the
contention period of the upstream channel. Once a
Probability-based Optimal Contention Window (P-OCW) is obtained,
we then proceed to allocate contention slots to the corresponding
flows. Such an allocation is prioritized based not only on class,
but also on price of the contending service flows. Additionally, a
price-based scheduling framework is developed to provide
price-differentiation among users. Our scheduling framework is
designed to work using TDD mode in order to take advantage of the
adaptive subframes size. Therefore, our structure dynamically
balances the downlink and uplink traffic. Furthermore, Deficit
Round Robin (DRR) and Distributed Deficit Round Robin (DDRR) are
deployed as the scheduling disciplines within the framework,
mainly because of their low complexity and ability to avoid
bandwidth starvation of lower-priority flows. Popular and widely
used schedulers, such as Priority Queue (PQ), Weighted Fair
Queuing (WFQ), First In First Out (FIFO), DRR, DDRR are tested and
compared with our schedulers, i.e., Adaptive Price-based Deficit
Round Robin (AP-DRR) and Adaptive Price-based Distributed Deficit
Round Robin (AP-DDRR). A straightforward rate-based connection
admission control policy is also proposed to be implemented along
with the framework. Simulation experiments are carried in order to
demonstrate the accuracy and effectiveness of our proposed
framework in terms of QoS. From simulation results, we conclude
that the use of our contention slot allocation algorithm and the
adaptive price-based scheduling framework is strongly recommended.

This thesis proposes a Quality of Service (QoS) architecture for
IEEE 802.16, which includes a contention period management
algorithm and a price-based scheduling framework. We first derive
the optimal contention window size to properly manage the
contention period of the upstream channel. Once a
Probability-based Optimal Contention Window (P-OCW) is obtained,
we then proceed to allocate contention slots to the corresponding
flows. Such an allocation is prioritized based not only on class,
but also on price of the contending service flows. Additionally, a
price-based scheduling framework is developed to provide
price-differentiation among users. Our scheduling framework is
designed to work using TDD mode in order to take advantage of the
adaptive subframes size. Therefore, our structure dynamically
balances the downlink and uplink traffic. Furthermore, Deficit
Round Robin (DRR) and Distributed Deficit Round Robin (DDRR) are
deployed as the scheduling disciplines within the framework,
mainly because of their low complexity and ability to avoid
bandwidth starvation of lower-priority flows. Popular and widely
used schedulers, such as Priority Queue (PQ), Weighted Fair
Queuing (WFQ), First In First Out (FIFO), DRR, DDRR are tested and
compared with our schedulers, i.e., Adaptive Price-based Deficit
Round Robin (AP-DRR) and Adaptive Price-based Distributed Deficit
Round Robin (AP-DDRR). A straightforward rate-based connection
admission control policy is also proposed to be implemented along
with the framework. Simulation experiments are carried in order to
demonstrate the accuracy and effectiveness of our proposed
framework in terms of QoS. From simulation results, we conclude
that the use of our contention slot allocation algorithm and the
adaptive price-based scheduling framework is strongly recommended.

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