A latency-aware scheduling algorithm for all-optical packet switching networks with FDL buffers

Abstract

Optical buffers implemented by fiber delay lines (FDLs) have a volatile nature due to signal loss and noise accumulation. Packets suffer from excessive recirculation through FDLs, and they may be dropped eventually in their routing paths. Because of this, packet scheduling becomes more difficult in FDL buffers than in RAM buffers, and requires additional design considerations for reducing packet loss. We propose a latency-aware scheduling scheme and an analytical model for all-optical packet switching networks with FDL buffers. The latency-aware scheduling scheme is intended to minimize the packet loss rate of the networks by ranking packets in the optimal balance between latency and residual distance. The analytical model is based on non-homogeneous Markovian analysis to study the effect of the proposed scheduling scheme on packet loss rate and average delay. Furthermore, our numerical results show how various network parameters affect the optimal balance. We demonstrate quantitatively how to achieve the proper balance between latency and residual distance so that the network performance can be improved significantly. For instance, we find that under a given latency limit and light traffic load our scheduling scheme achieves a packet loss rate 71% lower than a scheduling scheme that ranks packets simply based on latency

Security-Aware Packet Scheduling Scheme with Multi-Level Queuing and RSA

“…The latency aware scheduling was intended to minimize the packet loss rate of the networks by ranking packets in the optimal balance between latency and residual distance. The analytical model was based on non-homogeneous Markovian analysis to study the effect of packet loss rate and average delay [6].Meneguette et al proposed an online packet scheduling model. It was based on vehicular network applications.…”

An analytical model for input-buffered optical packet switches with reconfiguration overhead

“…Switches are reconfigured cyclically, and packets are selected in each cycle for transmission from input buffers to outputs. The analytical model is based on Markovian analysis [1,3,4,6,11,28], and is suitable for round-robin scheduling schemes in which only non-empty VOQs [21] are served or all VOQs are served. The numerical analysis demonstrates how various scheduling schemes and network parameters affect the optimal reconfiguration frequency.…”