Multicast Scheduling for Input-Queued Switches

The demand for network bandwidth is growing much faster than the increase in commercially available memory bandwidth, causing a growing interest in input-queued switches. Furthermore, an increase in the proportion of multicast traffic in today's networks makes it important that they support such traffic efficiently. This paper presents the design of the scheduler for an MxN input-queued multicast switch. It is assumed that: (i) Each input maintains a single queue for arriving multicast cells, and (ii) Only the cell at the head of line (HaL) can be observed and scheduled at one time. The scheduler is required to be: (i) Work-conserving, which means that no output port may be idle as long as there is an input cell destined to it, and (ii) Fair, which means that no input cell may be held at HaL for more than a fixed number of cell times. The aim of our work is to find a work-conserving, fair policy that delivers maximum throughput and minimizes input queue latency, and yet is simple to implement in hardware. When a scheduling policy decides which cells to schedule, contention may require that it leave a residue of cells to be scheduled in the next cell time. The selection of where to place the residue uniquely defines the scheduling policy. Subject to a fairness constraint, it is demonstrated that a policy which always concentrates the residue on as few inputs as possible outperforms all other policies. There is a tradeoff between concentration of residue (for high throughput), strictness of fairness (to prevent starvation), and implementationl simplicity (for the design of high-speed switches). By mapping the general multicast switching problem onto a variation of the popular block-packing game, Tetris, we are able to analyze, in an intuitive and geometric fashion, various scheduling policies which possess these attributes in different proportions. We pr~sent a novel scheduling policy, called TATRA, which performs extremely well and is strict in fairness. We also present a simple weight based algorithm, called WBA, that is simple to implement in hardware, fair, and performs well when compared to a concentrating algorithm.