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SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
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Computer Communications
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On the performance of greedy algorithms in packet buffering
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IEEE Transactions on Parallel and Distributed Systems
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NOCS '07 Proceedings of the First International Symposium on Networks-on-Chip
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NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
Packet buffering: randomization beats deterministic algorithms
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
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We present a simple and near optimal randomized parallel scheduling algorithm for scheduling packets in routers based on the Switch-Memory-Switch (SMS)architecture, which emulates 'output queuing' by using a collection of small memories within the switch to buffer packets, and which forms the basis of the fastest routers in use today. For a router with N inputs and N outputs, our algorithm computes the schedule in O(log* N) rounds, where a round is a communication of a few bits between input ports and memory together with simple local computation at the inputs and memory. Furthermore, by using an O(log* N) deep pipeline at each input, our algorithm computes the schedule in a constant number of rounds. Our pipelined algorithm is quite simple and achieves optimal (i.e.,constant) throughput with a tiny O(log* N) delay.We show that the total amount of buffer memory required by our algorithm is close to the minimum required. We also show that the number of buffer memories is within an εN additive term of 2N -- 1, for any positive constant ù0 (and is within an additive term of o(N)for the basic scheduler), where 2N -- 1 is the minimum number of memories needed under adversarial placement of packets. Furthermore we show that the number of extra memories that we use over the minimum of N that is required in the offline version, is within a constant factor of the minimum required by any on-line scheduler, even if that scheduler is allowed to fail occasionally.Our scheduling algorithm is randomized and works with high probability in N. We also prove that it has the 'self-stabilizing' property, i.e., it resumes its normal behavior if occasional lapses occur due to the probabilistic nature of the algorithm.