Scheduling with Soft Deadlines for Input Queued Switches

We study the problem of deadline aware scheduling for input queued (IQ) switches. While most research on scheduler design for IQ switches has focused on maximizing throughput and optimizing switch performance for non-realtime traffic, packet deadlines are a key consideration in the context of real-time applications like multimedia streaming and video telephony. In this paper, we introduce the notion of “soft deadlines” and study the scheduling problem within a dynamic programming (DP) framework. We demonstrate that by partitioning the set of switch configurations into “orthogonal” and “complete” subsets, the scheduling problem for an IQ switch can be transformed into one of scheduling parallel queues on a single server. We establish key structural properties of the optimal policy for the latter problem. We show that operating the switch using a single configuration subset is good enough to support any uniform admissible load. Further, we show that a scheduling policy which combines subset based operation with a randomized subset selection rule can support any admissible load. The randomized policy requires a Birkhoffvon Neumann (BV) decomposition of the input load vector. To eliminate this dependence, we propose two classes of heuristic scheduling policies, namely pMWM(τ )-LLF and pMWM(τ )MaxProj, which select the operational subset based on periodic maximum weight matching (pMWM). We demonstrate the efficacy of the proposed policies via simulations. The proposed policies have a computational complexity of only O(N) per time-slot, and outperform MWM under many scenarios.