55 research outputs found
On the Stability of Isolated and Interconnected Input-Queued Switches under Multiclass Traffic
In this correspondence, we discuss the stability of scheduling algorithms for input-queueing (IQ) and combined input/output queueing (CIOQ) packet switches. First, we show that a wide class of IQ schedulers operating on multiple traffic classes can achieve 100 % throughput. Then, we address the problem of the maximum throughput achievable in a network of interconnected IQ switches and CIOQ switches loaded by multiclass traffic, and we devise some simple scheduling policies that guarantee 100 % throughput. Both the Lyapunov function methodology and the fluid modeling approach are used to obtain our results
Sprinklers: A Randomized Variable-Size Striping Approach to Reordering-Free Load-Balanced Switching
Internet traffic continues to grow exponentially, calling for switches that
can scale well in both size and speed. While load-balanced switches can achieve
such scalability, they suffer from a fundamental packet reordering problem.
Existing proposals either suffer from poor worst-case packet delays or require
sophisticated matching mechanisms. In this paper, we propose a new family of
stable load-balanced switches called "Sprinklers" that has comparable
implementation cost and performance as the baseline load-balanced switch, but
yet can guarantee packet ordering. The main idea is to force all packets within
the same virtual output queue (VOQ) to traverse the same "fat path" through the
switch, so that packet reordering cannot occur. At the core of Sprinklers are
two key innovations: a randomized way to determine the "fat path" for each VOQ,
and a way to determine its "fatness" roughly in proportion to the rate of the
VOQ. These innovations enable Sprinklers to achieve near-perfect load-balancing
under arbitrary admissible traffic. Proving this property rigorously using
novel worst-case large deviation techniques is another key contribution of this
work
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