MNCM a new class of efficient scheduling algorithms for input-buffered switches with no speedup

In this paper, we use fluid model techniques to establish some new results for the throughput of input-buffered switches. In particular, we introduce a new class of deterministic maximal size matching algorithms that achieves 100% throughput. Dai and Prabhakar (2000) has shown that any maximal size matching algorithm with speedup of 2 achieves 100% throughput. We introduce a class of maximal size matching algorithms that we call them maximum node containing matching (MNCM) algorithms, and prove that they have 100% throughput with no speedup. We also introduce a new weighted matching algorithm, maximum first matching (MFM) with complexity O(N^2.5) that belongs to MNCM. MFM, to the best of our knowledge, is the lowest complexity deterministic algorithm that delivers 100% throughput. The only assumption on the input traffic is that it satisfies the strong law of large numbers. Besides throughput, average delay is the other key performance metric for the input-buffered schedulers. We use simulation results to compare and study the delay performance of MFM. The simulation results demonstrate promising delay performance for MFM.