By introducing storage into Optical Circuit Switched (OCS) networks and storing delay-tolerant requests until off-peak hours, the networks can have better performance. Since scheduling a data transfer in SnF networks has to deal with the spatial and temporal arrangement of the request, it is much more complicated than the routing-alone problem. In our prior research, we proposed TS-MLG, a holistic approach to solve this problem, but the computational and spatial complexity of the approach is high, limiting its use in large scale networks. In this paper, we propose a decoupled solution and specific algorithms for both sub-problems. The solutions can reduce spatial and computational complexity from O(N²*L²) to O(N*L) with marginal sacrifice on network performance, in which N and L are respectively the number of network nodes and state changes in the network. Simulation results show that in a moderate sized network with frequent state changes, the computing time of request scheduling can be reduced by 600 times. We conclude that the decoupled SnF scheduling has the potential of analyzing SnF in large networks with frequent state changes.

通过将存储引入光电路交换（OCS）网络并存储容忍延迟的请求直到非高峰时段，网络可以具有更好的性能。由于在SnF网络中安排数据传输必须处理请求的空间和时间安排，因此它比仅路由问题要复杂得多。在我们先前的研究中，我们提出了TS-MLG，一种用于解决此问题的整体方法，但是该方法的计算和空间复杂度很高，限制了其在大规模网络中的使用。在本文中，我们针对这两个子问题提出了解耦解决方案和特定算法。这些解决方案可以将空间和计算复杂度从O （N ² * L ²）降低到O（N * L），但对网络性能的影响很小，其中N和L分别是网络节点数和网络状态变化。仿真结果表明，在状态变化频繁的中等规模网络中，请求调度的计算时间可减少600倍。我们得出的结论是，解耦的SnF调度具有分析状态频繁变化的大型网络中SnF的潜力。