# Time Shared Optical Network (TSON): A Programmable Network Edge Solution for Multi-Access Support
## 3 TSON, Present
### The TSON Testbed Setup and Experimental Results  
Xilinx vcu108 evaluation board is employed for this implementation. Figure 13a shows the TSON edge node, which is a Xilinx FPGA board connected to a server and receiving the SDN control plane  
Figure 12: The TSON edge node current data plane architecture. m + n - 1 = number of 10 G input–outputs (IOs).  
command via peripheral component interconnect express (PCIe). The FPGA board is connected to two FPGA mezzanine cards (FMCs) to provide \(16\times 10\) Gb (\(\mathrm{m}+\mathrm{n}-1=16\)) IOs. Figure 13b shows the testbed setup architecture with two TSON edge nodes. The edge nodes are connected to \(6\times 10\) Gbps ethernet traffic analysers from one side and from the other side to Smart Internet Lab's 5G test network. The 10 Gbps traffic streams can be aggregated to 10 or 100 Gbps traffic that is both sent to the metro network on the basis of different control policies.  
The Smart Internet Lab's 5G test network (5 GUK test network) has its core in the HPN lab at the University of Bristol. The test network serves several nodes in Bristol, as well as the Roman Baths in city of Bath, in providing access points for end user terminals connectivity for experimentation. Figure 14 presents the 5 GUK test network locations we have used to make a ring topology for the evaluation scenarios. Note that the ring topology is approximately 8 km.  
We have validated the functionality of the TSON edge nodes by applying different control policies on the fly using the SDN controller for both aggregated 10 and 100 Gb lines at the same time. Two different scenarios were considered for the experimental evaluation of the edge nodes. The first scenario involved back-to-back connection of two TSON edge nodes with standard single mode fibre (SSMF). In the second scenario, the proposed nodes were evaluated over the 5 GUK test network with 8 km of optical fibre. We evaluated the nodes using a fixed frame of 1500 B length. We used fine granularity to evaluate the edge nodes. In the fine granularity case, the T  
Figure 14: The Smart Internet Lab’s 5G test network (5 GUK test network) ring topology to evaluate the TSON edge nodes. HPN: High Performance Networks.  
Figure 13: Testbed setup: (**a**) TSON edge node; (**b**) the TSON edge nodes testbed setup architecture.  
same as the Ethernet frames, that is, 1500 B in length. For the sake of performance analysis, one 4 Gb and one 4.5 Gb client frames were converged to a 10 Gb line. Four 9.8 Gb clients were converged to a 100 Gb line. The Ethernet performance parameters under consideration included bit error rate (BER) and latency. Latency is defined as the time difference between the arrival of a frame at the analyser, and its departure from the analyser.  
Table 1 presents the latencies for the mentioned scenarios. This table shows that each TSON convergence node took 4.43 and 3.16 \(\upmu\)s for 10 Gb convergence and 100 Gb convergence, respectively. The back-to-back latency was 8.86 \(\upmu\)s for 10 G convergence, which was 2.54 \(\upmu\)s more than 100 G convergence. Further measurements have been taken to find out the reason. An edge node consists of 10 Gb IP cores, TSON pipelines, and 100 Gb IP core. We have measured the latency for individual components. Figure 15 shows the measurement result for 100 G convergence. In this scenario, frames passed one 10 Gb IP core, TSON pipelines, and one 100 Gb IP core. As can be seen in Figure 15, the TSON pipelines' latency was approximately the same as the 10 Gb IP core, and the 100 Gb IP core latency was much less than the 10 Gb IP core. The TSON pipelines' latency was approximately 1.5 \(\upmu\)s, which is very low. Figure 16 shows the BER for the evaluation scenarios. As it can be seen in this figure, the penalty was negligible for both 10 and 100 Gb convergence scenarios.