Throughput-Optimal Scheduling Design With Regular Service Guarantees in Wireless Networks

Motivated by the regular service requirements of video applications for improving quality of experience (QoE) of users, we consider the design of scheduling strategies in multihop wireless networks that not only maximize system throughput but also provide regular interservice times for all links. Since the service regularity of links is related to the higher-order statistics of the arrival process and the policy operation, it is challenging to characterize and analyze directly. We overcome this obstacle by introducing a new quantity, namely the time-since-last-service (TSLS), which tracks the time since the last service. By combining it with the queue length in the weight, we propose a novel maximum-weight-type scheduling policy, called Regular Service Guarantee (RSG) Algorithm. The unique evolution of the TSLS counter poses significant challenges for the analysis of the RSG Algorithm. To tackle these challenges, we first propose a novel Lyapunov function to show the throughput optimality of the RSG Algorithm. Then, we prove that the RSG Algorithm can provide service regularity guarantees by using the Lyapunov-drift-based analysis of the steady-state behavior of the stochastic processes. In particular, our algorithm can achieve a degree of service regularity within a factor of a fundamental lower bound we derive. This factor is a function of the system statistics and design parameters and can be as low as two in some special networks. Our results, both analytical and numerical, exhibit significant service regularity improvements over the traditional throughput-optimal policies, which reveals the importance of incorporating the metric of time-since-last-service into the scheduling policy for providing regulated service.