Fair Real-Time Traffic Scheduling over a Wireless LA

Unpredictable wireless channel errors may cause applications with real-time traffic to receive degraded quality of services due to packet losses. In the presence of such errors, a challenging problem is how to schedule packets to achieve fairness among real-time flows and to maximize the overall system throughput simultaneously. We capture fairness by minimizing the maximum degradation in service over all flows. In this paper, we show that no online algorithm can guarantee a bounded performance ratio with respect to the optimal algorithm. We then compare four different online algorithms and evaluate them using simulations. The first two are EDF (Earliest Deadline First) and GDF (Greatest Degradation First) that consider only one aspect of our scheduling goal respectively. EDF is naturally suited for maximizing throughput while GDF seeks to minimize the maximum degradation. The next two are algorithms, called EOG (EDF or GDF) and LFF (Lagging Flows First), that consider the two aspects of our scheduling goal. EOG simply combines EDF and GDF, whereas LFF tries to favor lagging flows in a non-trivial manner. Our simulation results show that LFF is almost as good as EDF in maximizing the throughput and also is better than GDF in minimizing the maximum degradation. Finally, we also show that there is an optimal polynomial time algorithm for the offline version of the problem.