Quality of service management algorithms in WiMAX networks

The IEEE 802.16 standard, popularly known as WiMAX, addresses broadband access technology for Wireless Metropolitan Area Networks (WMANs). It is anticipated to be a viable alternative to traditional wired broadband techniques due to its cost-competitiveness, ubiquitous access, and Quality of Service (QoS) capabilities. Because it is a wireless technology, in which resources are limited such as bandwidth and power; how to manage these resources while maintaining QoS to diverse applications become a critical issue. Therefore, efficient admission control, scheduling, and power saving schemes are essential in this network. Four algorithms have been proposed and developed in this research. Firstly, a QoS-Aware CAC scheme for Mobile WiMAX networks is proposed to prevent the starvation problem of the highest and the lowest service classes due to the linear adaptation technique used to accommodate more users into the network as well as inefficient bandwidth utilization because of the way the adaptive reserved bandwidth threshold for handoff is adjusted. This scheme determines an admission criteria based on scheduling service classes. In the admission criteria, a bandwidth-degradation policy is used to admit more users in order to prevent starvation. An adaptive threshold has been introduced dynamically to adjust the reserved bandwidth threshold for handoff connections based on the traffic intensity of handoff requests to improve bandwidth utilization. In addition, an analytical model for the proposed scheme is developed. Secondly, a Load-Aware Weighted Round Robin algorithm (LAWRR) packet scheduling discipline for downlink traffic in 802.16 networks is proposed to improve the poor performance of scheduling algorithm that use static weights under bursty traffic. It dynamically determines the weight of each queue in the various classes based on current traffic characteristics and the static weight at the beginning of each base-station round. Thirdly, an energy algorithm called the Efficient Battery Life-aware Power Saving (EBLAPS) algorithm is proposed to address the problems of minimizing energy at the expense of response due to how energy sleep parameters are adjusted based on the residual energy and the use of standard sleep mode algorithms consumes high energy because of frequent transition to listening mode in the case of light traffic. The energy sleep parameters: idle threshold,initial sleep parameters and final sleep parameters are adjusted according to the downlink stochastic traffic arrival pattern of a mobile station (MS) in order to reduce the high response delay as well as the high energy consumption. Moreover, an improved sleep mode control algorithm has been introduced to reduce the high energy consumption of the standard sleep mode algorithm. Simulation have been extensively used to evaluate the proposed algorithm. Finally, Discrete Event Simulator (DES) is designed and developed in order to evaluate the performance of the proposed algorithms. The DES is validated by comparing its results with the results obtained from Qualnet, OPNET,and C simulators. Substantial simulations have been extensively conducted to evaluate the performance of the proposed algorithms in comparison to the existing bandwidth and power management algorithms. Simulation results illustrate that the proposed QoS-Aware CAC scheme outperforms the compared schemes significantly in terms of reducing the New Connection Blocking Probability (NCBP), Handoff Connection Dropping Rate (HCDP), and also increase the throughput of the highest and the lowest service classes as well as the numerical results show similar performance with the simulation results. The results also show that the proposed LAWRR algorithm reduces average delay and packet loss. Furthermore, the results also show that the proposed EBLAPS algorithm outperforms the compared schemes significantly in terms of both the average response delay and the average energy consumption. The results show that the proposed algorithms provide enhanced efficient bandwidth and power utilization, grant more connections, assure QoS guarantees to all service classes, and also extend the battery life