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-.. _mlrsearch_algorithm:
-
-MLRsearch Tests
----------------
-
-Overview
-~~~~~~~~
-
-Multiple Loss Rate search (MLRsearch) tests use new search algorithm
-implemented in FD.io CSIT project. MLRsearch discovers any number of packet
-throughput rates in a single search, with each rate associated with a
-different Packet Loss Ratio (PLR) criteria.
-
-Two throughput rates of interest in FD.io CSIT are Non-Drop Rate (NDR,
-with zero packet loss, PLR=0) and Partial Drop Rate (PDR, with packet
-loss rate not greater than the configured non-zero PLR, currently 0.5%).
-
-MLRsearch discovers all the rates in a single pass, reducing required time
-duration compared to separate `binary search`_es for each rate. Overall
-search time is reduced even further by relying on shorter trial
-durations of intermediate steps, with only the final measurements
-conducted at the specified final trial duration. This results in the
-shorter overall execution time when compared to standard NDR/PDR binary
-search, while guaranteeing similar results.
-
-.. Note:: All throughput rates are *always* bi-directional
- aggregates of two equal (symmetric) uni-directional packet rates
- received and reported by an external traffic generator.
-
-Search Implementation
-~~~~~~~~~~~~~~~~~~~~~
-
-Detailed description of the MLRsearch algorithm is included in the IETF
-draft `draft-ietf-bmwg-mlrsearch-01
-<https://datatracker.ietf.org/doc/html/draft-ietf-bmwg-mlrsearch-01>`_
-that is in the process of being standardized in the IETF Benchmarking
-Methodology Working Group (BMWG).
-
-MLRsearch is also available as a `PyPI (Python Package Index) library
-<https://pypi.org/project/MLRsearch/>`_.
-
-Implementation Deviations
-~~~~~~~~~~~~~~~~~~~~~~~~~
-
-FD.io CSIT implementation of MLRsearch is currently fully based on the -01`
-version of the `draft-ietf-bmwg-mlrsearch
-<https://datatracker.ietf.org/doc/html/draft-ietf-bmwg-mlrsearch-01>`_,
-the PyPI version is slightly older.
-
-.. _binary search: https://en.wikipedia.org/wiki/Binary_search