Modelling and performance analysis of the distributed scheduler in IEEE 802.16 mesh mode
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
Proceedings of the 12th annual international conference on Mobile computing and networking
Scheduling algorithms for multi-carrier wireless data systems
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Adaptive network coding and scheduling for maximizing throughput in wireless networks
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Proceedings of the 14th ACM international conference on Mobile computing and networking
Delay constrained uplink scheduling policy for rtPS-ertPS service in IEEE 802.16e BWA systems
International Journal of Communication Systems
Jamming resistant architecture for WiMAX mesh network
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Joint congestion control, routing, and MAC for stability and fairness in wireless networks
IEEE Journal on Selected Areas in Communications
Hi-index | 0.00 |
WiMAX distributed scheduling can be modeled as two procedures: three-way handshaking procedure and data subframe scheduling procedure. Due to manipulating data transmission directly, data subframe scheduling has a closer relationship with user Quality of Service (QoS) satisfaction, and has more severe impact on network performance, compared with handshaking procedure. A QoS guaranteed Throughput-Efficiency Optimal distributed data subframe Scheduling scheme, named as QoS-TEOS, is proposed. QoS-TEOS achieves QoS guarantee through modeling services into different ranks and assigning them with corresponding priorities. A service with higher priority is scheduled ahead of that with lower priority and offered with high QoS quality. Same kinds of services that request similar QoS quality are classified into one service set. Different service sets are scheduled with different strategies. QoS-TEOS promotes network performance through improving network throughput and efficiency. Theoretical analysis shows that the scheduled data transmission should balance data generation rate from upper layer and transmission rate of physical layer, to avoid network throughput and efficiency declining. Simulation results show that QoS-TEOS works excellently to achieve throughput-efficiency optimization and guarantee a high QoS.