Traditional OTN technologies are mainly used on backbone and metro networks to carry services at a rate higher than 1 Gbit/s. After OTN devices are deployed on metro or access networks, the following challenges emerge: inelastic pipes (ODU0 at minimum), small number of connections, and inflexible bandwidth adjustment.
With the optical service unit flexible container (OSUflex), Liquid OTN optimizes the multiplexing and mapping paths, so that the OSUflex can be directly mapped to the higher-order pipes to satisfy different service bandwidth requirements.
- OSUflex over ODUflex: coexistence and interworking with existing OTN or DWDM networks
- OSUflex over ODUCn: new Liquid OTN networks
With the Liquid OTN technology, an OPUk payload in an existing OTN system is divided into physically isolated communication pipes with a fixed frame length. The OPUk/flex payload area is divided into multiple payload blocks (PBs). The following figure uses OPU4 as an example.
- When multiple channels of OSUflex signals are mapped and multiplexed into OPUk/flex payloads, a 12-bit tributary port number (TPN) needs to be added based on each channel of OSUflex signals to identify the mapping between each channel of OSUflex signals and tributaries.
- A TPN must be unique at the server layer to ensure that the receive end can correctly distinguish tributary port numbers. The TPN function is similar to the MSI function of OTN, and is a preferred manner. To be specific, a TPN is added based on the OSUflex frame to exactly form a PB.
- Ubiquitous all-optical connectivity: Liquid OTN introduces OSUflex containers to support flexible bandwidth definition. Furthermore, network hard slices can achieve a fine granularity of 2 Mbit/s, bringing 500 times more connections.
- Hitless bandwidth adjustment: Supports hitless bandwidth adjustment from 2 Mbit/s to 100 Gbit/s, ensuring zero service interruption and full use of network resources. e connections.
- Ultra-low transmission latency: Significantly reduces the network transmission layers, provides differentiated latency levels, and reduces per-site latency by 70% to reach the microsecond level, adapting to different latency-sensitive scenarios.
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