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Source publication
This paper investigates packet loss in multi-service Optical Packet Switched (OPS) networks, in which the Preemptive Drop Policy (PDP) is adopted to implement QoS differentiation. A novel approximation model is proposed. In contrast with existing multi-dimensional Markov model, which focuses on analyzing the small system with only two service class...
Context in source publication
Context 1
... OPS nodes inside the studied OPS network have the same switching architecture. We consider the asynchronous bufferless OPS switch with no internal blocking. As shown in Fig. 1, the switch architecture consists of input/output fibers. Each fiber offers different wavelengths with capacity as Gbps. When a packet arrives, the packet header is extracted and processed by the control module electronically. While the header is processed, the packet payload is buffered using FDLs located at the input. Based on the ...
Citations
This paper presents two separate Markov models to investigate blocking probabilities in multi-service communications systems, when preemptive scheduling is adopted to implement service differentiation. One is the generalized model, which is built as a multi-dimensional Markov chain, based on a variant of the multi-dimensional Erlang loss model. The other is the hierarchical model, which is constructed as a multi-level Markov chain, based on a combination of one-dimensional Erlang loss models. A detailed comparison when applying these two models to a general R-service communications system is presented. This validates the major advantages of the proposed hierarchical model: the closed form expressions of blocking probabilities; the dramatically reduced computational complexity; and the excellent scalability for analyzing larger systems. Furthermore, the analytical values are compared with simulation results for two- and three-service systems. Results show that the proposed hierarchical model provides a high degree of accuracy in the blocking probabilities under different scenarios, especially when the relative arrival rates of the lower priority classes are high.
