Abstract

Optical flow switching (OFS) has been recently introduced as a potential “green” architecture addressing the power issue of store-and-forward packet switching in future MAN-WAN Terabit networks. One key architectural component of OFS differentiating it from other “green” WAN architectures such as optical circuit switching (OCS), optical packet switching (OPS) and optical burst switching (OBS), is its centralized flow scheduling. Comparing the theoretical network capacity regions of OFS, OCS, OPS and OBS has revealed that the dominating theoretical capacity depends on the hardware as well as on the port configuration. The dominating actual capacity (throughput) that can be achieved also depends on the flow schedulers supported by each architecture. Since centralized scheduling incorporated in OFS is the least restricting between all scheduling methods, OFS is a promising “green” architecture option for future MAN-WAN Terabit networks. For better understanding the actual potential throughput of OFS, we study its scheduling problem in a realistic traffic model where lightpath requests arrive as a time-dependent Poisson process with Pareto distributed lightpath service times. Lightpath schedules are taken at fixed time intervals (larger than 100 ms) in a central node and flows that have already been scheduled cannot be interrupted before their completion. The scheduling problem is represented as a discrete-time Markov decision process where the objective function is given by the flow blocking probability over a finite time horizon. We derive three lower bounds to the objective function and propose several schedulers, with and without fairness requirements. The performance of our OFS schedulers are evaluated under both static and limited dynamic routing, by emulating the algorithms on random network topologies for two hours. The main result is that our proposed max-min fair scheduler with limited dynamic routing significantly outperforms all other schedulers with static routing. Furthermore, its blocking probability is close to the lower bound for static routing.

© 2011 IEEE

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