oopt-gnpy/docs/intro.rst

.. _intro:

Introduction
============

``gnpy`` is a library for building route planning and optimization tools.

It ships with a number of example programs. Release versions will ship with
fully-functional programs.

    **Note**: *If you are a network operator or involved in route planning and
    optimization for your organization, please contact project maintainer Jan
    Kundrát <jkt@jankundrat.com>. gnpy is looking for users with
    specific, delineated use cases to drive requirements for future
    development.*

This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power,
or to run a planning script to check SNR of several services:

.. image:: images/gnpy-transmission-example.svg
   :width: 100%
   :align: left
   :alt: Running a simple simulation example

By default, the gnpy-transmission-example script operates on a single span network defined in
`gnpy/example-data/edfa_example_network.json <../gnpy/example-data/edfa_example_network.json>`_

You can specify a different network at the command line as follows. For
example, to use the CORONET Global network defined in
`gnpy/example-data/CORONET_Global_Topology.json <../gnpy/example-data/CORONET_Global_Topology.json>`_:

.. code-block:: shell-session

    $ gnpy-transmission-example $(gnpy-example-data)/CORONET_Global_Topology.json

It is also possible to use an Excel file input (for example
`gnpy/example-data/CORONET_Global_Topology.xls <../gnpy/example-data/CORONET_Global_Topology.xls>`_).
The Excel file will be processed into a JSON file with the same prefix.
Further details about the Excel data structure are available `in the documentation <excel.rst>`__.

The main transmission example will calculate the average signal OSNR and SNR
across network elements (transceiver, ROADMs, fibers, and amplifiers)
between two transceivers selected by the user. Additional details are provided by doing ``gnpy-transmission-example -h``. (By default, for the CORONET Global
network, it will show the transmission of spectral information between Abilene and Albany)

This script calculates the average signal OSNR = |OSNR| and SNR = |SNR|.

.. |OSNR| replace:: P\ :sub:`ch`\ /P\ :sub:`ase`
.. |SNR| replace:: P\ :sub:`ch`\ /(P\ :sub:`nli`\ +\ P\ :sub:`ase`)

|Pase| is the amplified spontaneous emission noise, and |Pnli| the non-linear
interference noise.

.. |Pase| replace:: P\ :sub:`ase`
.. |Pnli| replace:: P\ :sub:`nli`

Further Instructions for Use
----------------------------

Simulations are driven by a set of `JSON <json.rst>`__ or `XLS <excel.rst>`__ files.

The ``gnpy-transmission-example`` script propagates a spectrum of channels at 32 Gbaud, 50 GHz spacing and 0 dBm/channel. 
Launch power in fiber spans can be overridden by using the ``--power`` argument.
Spectrum information is not yet parametrized but can be modified directly in the ``eqpt_config.json`` (via the ``SpectralInformation`` -SI- structure) to accommodate any baud rate or spacing.
The number of channel is computed based on ``spacing`` and ``f_min``, ``f_max`` values.

An experimental support for Raman amplification is available:

.. code-block:: shell-session

     $ gnpy-transmission-example \
       $(gnpy-example-data)/raman_edfa_example_network.json \
       --sim $(gnpy-example-data)/sim_params.json --show-channels

Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <../gnpy/example-data/raman_edfa_example_network.json>`_.
General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <../gnpy/example-data/sim_params.json>`_.

Use ``gnpy-path-request`` to request several paths at once:

.. code-block:: shell-session

     $ cd $(gnpy-example-data)
     $ gnpy-path-request -o output_file.json \
       meshTopologyExampleV2.xls meshTopologyExampleV2_services.json

This program operates on a network topology (`JSON <json.rst>`__ or `Excel <excel.rst>`__ format), processing the list of service requests (JSON or XLS again).
The service requests and reply formats are based on the `draft-ietf-teas-yang-path-computation-01 <https://tools.ietf.org/html/draft-ietf-teas-yang-path-computation-01>`__ with custom extensions (e.g., for transponder modes).
An example of the JSON input is provided in file `service-template.json`, while results are shown in `path_result_template.json`.

Important note: ``gnpy-path-request`` is not a network dimensionning tool: each service does not reserve spectrum, or occupy ressources such as transponders. It only computes path feasibility assuming the spectrum (between defined frequencies) is loaded with "nb of channels" spaced by "spacing" values as specified in the system parameters input in the service file, each cannel having the same characteristics in terms of baudrate, format,... as the service transponder. The transceiver element acts as a "logical starting/stopping point" for the spectral information propagation. At that point it is not meant to represent the capacity of add drop ports.
As a result transponder type is not part of the network info. it is related to the list of services requests.

The current version includes a spectrum assigment features that enables to compute a candidate spectrum assignment for each service based on a first fit policy. Spectrum is assigned based on service specified spacing value, path_bandwidth value and selected mode for the transceiver. This spectrum assignment includes a basic capacity planning capability so that the spectrum resource is limited by the frequency min and max values defined for the links. If the requested services reach the link spectrum capacity, additional services feasibility are computed but marked as blocked due to spectrum reason.

OpenROADM networks can be simulated via ``gnpy/example-data/eqpt_config_openroadm_*.json`` -- see ``gnpy/example-data/Sweden_OpenROADM*_example_network.json`` as an example.