Abstract
Input Queued switches have been very well studied in the recent past. The Maximum Weight Matching (MWM) algorithm is known to deliver 100% throughput under any admissible traffic. However, MWM is not practical for its high computational complexity O(N 3). In this paper, we study a class of approximations to MWM from the point of view of local search. Firstly, we propose a greedy scheduling algorithm called GSA. It has the following features: (a) It is very simple to compute the weight of a neighbor matching. GSA only needs to compute the weight of two swapped edges instead of the weight of all the edges. (b) The computational complexity of GSA is O(c_max), where c_max denotes the maximum number of iterations. Hence we can adjust the value of c_max to achieve low computational complexity. Secondly, we observe that: (a) Local search is well suitable for parallel computing. (b) Each line card of high performance router has at least one processor. Based on the two important observations, we develop the second algorithm PGSA. Compared with GSA, PGSA significantly reduce the number of iterations. Simulation results show that PGSA with three iterations outperforms algorithms in [1] under different switch sizes.
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© 2005 Springer-Verlag Berlin Heidelberg
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Zheng, Y., He, S., Sun, S., Gao, W. (2005). Scheduling Algorithms for Input Queued Switches Using Local Search Technique. In: Lorenz, P., Dini, P. (eds) Networking - ICN 2005. ICN 2005. Lecture Notes in Computer Science, vol 3420. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31956-6_102
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DOI: https://doi.org/10.1007/978-3-540-31956-6_102
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25339-6
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