Quality-Driven Capacity-Aware Resources Optimization Design for Ubiquitous Wireless Networks

In this paper, we propose a probability-statistical capacity-prediction scheme to provide probabilistic quality-of-service (QoS) guarantees under the high traffic load of IEEE 802.11 wireless multimedia Mesh networks. The proposed scheme perceives the state of wireless link based on the MAC retransmission statistics and calculates the statistical channel capacity especially under the saturated traffic load. Via a cross-layer design approach, the scheme allocates network resource and forwards data packets by taking the interference among flows and the channel capacity into consideration. Extensive experiments have been carried out on the basis of IEEE 802.11 protocols in order to demonstrate the superiority of the proposed scheme over the existing location-based QoS optimization delivery algorithm in terms of retransmission count, successful delivery rate, and end-to-end delay on the condition of time-varying multi-hop wireless links.