Energy efficient scheduling with QoS guarantee for IEEE 802.16e broadband wireless access networks
IWCMC '07 Proceedings of the 2007 international conference on Wireless communications and mobile computing
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Maximizing Unavailability Interval for Energy Saving in IEEE 802.16e Wireless MANs
IEEE Transactions on Mobile Computing
Power-saving scheduling with a QoS guarantee in a mobile WiMAX system
Journal of Network and Computer Applications
Joint optimization of power saving mechanism in the IEEE 802.16e mobile WiMAX
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
A power saving scheduling algorithm for multiple MSSs in large-scale IEEE 802.16e environments
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Vacation policy optimization with application to IEEE 802.16e power saving mechanism
WD'09 Proceedings of the 2nd IFIP conference on Wireless days
Switching cost minimization in the IEEE 802.16e mobile WiMAX sleep mode operation
Wireless Communications & Mobile Computing
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This paper studies an optimization problem for real-time flows scheduling with QoS guarantees over IEEE 802.16e WiMAX networks. Each mobile station may have one or more real-time flows that have specific QoS requirements, including bandwidth requirements and delay bounds. Since flows have different arrival rates, the mobile station turns off the transceiver and enters sleep mode to save energy only when it does not need to either receive or send traffic. For minimizing the energy consumption, we are required to schedule all flows efficiently according to the QoS requirements to increase the sleep interval. We formulate the scheduling problem as an Integer Linear Program (ILP) to minimize the total number of active frames to save energy consumption. A heuristic algorithm, called adaptive bandwidth reservation (ABR), is also proposed to improve the computing efficiency. The approximation factor of 2 is proved in the worst case analysis of the ABR algorithm. Our approaches not only guarantee the QoS for real-time flows, but also minimize energy consumption of mobile stations. The proposed approach provides significant improvement on throughput and energy saving for the mobile station. Experiment results demonstrate that the ABR algorithm outperforms the previous approaches in terms of energy saving, bandwidth utilization and drop rate.