Distortion optimized multi-service scheduling for next-generation wireless mesh networks

Distributing multimedia content over wireless networks is challenging due to the limited resource availability and the unpredictability of wireless links. As more and more users demand wireless access to (real-time) multimedia services, the impact of constrained resources is different for different media types. Therefore, understanding this impact and developing mechanisms to optimize content delivery under resource constraints according to user perception will be key in improving user satisfaction. In this paper, we develop a novel scheduling algorithm for multi-hop wireless networks, which optimizes packet delivery for multiple audio, video and data flows according to user perceivable quality metrics. We formulate a multidimensional optimization problem to minimize the overall distortion while satisfying resource constraints for the wireless links. Our Quality-of-Experience (QoE)-optimized scheduler makes use of models to determine the user's perception of quality that are specific to the type of service being provided. Our experimental results, obtained with the NS-2 IEEE 802.16 MESH-mode simulator, show that distortion-aware scheduling can significantly increase the perceived quality of multimedia streaming under bandwidth constraints. As the scheduler allows the modeling of fairness constraints among multiple competing flows, we also demonstrate an improvement in fairness across different flows.