Laxity-Based Opportunistic Scheduling with Flow-Level Dynamics and Deadlines
Many data applications in the next generation cellular networks, such as content pre-caching and video progressive downloading, require flow-level Quality of Service (QoS) guarantees. One such requirement is deadline, where the transmission task needs to be completed before the application-specific time. To minimize the number of uncompleted transmission tasks, the authors study laxity-based scheduling policies in this paper. They propose a Less-Laxity-Higher-Possible-Rate (L2HPR) policy and prove its asymptotic optimality in under-loaded identical-deadline systems. The asymptotic optimality of L2HPR can be applied to estimate the schedulability of a system and provide insights on the design of scheduling policies for general systems.