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A near optimal scheduler for switch-memory-switch routers
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Source ACM Symposium on Parallel Algorithms and Architectures archive
Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures table of contents
San Diego, California, USA
SESSION: Networks III table of contents
Pages: 343 - 352  
Year of Publication: 2003
ISBN:1-58113-661-7
Authors
Adnan Aziz  The University of Texas at Austin, Austin, TX
Amit Prakash  The University of Texas at Austin, Austin, TX
Vijaya Ramachandra  The University of Texas at Austin, Austin, TX
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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ABSTRACT

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 ù>0 (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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Adnan Aziz: colleagues
Amit Prakash: colleagues
Vijaya Ramachandra: colleagues