diff options
author | Maciek Konstantynowicz <mkonstan@cisco.com> | 2019-05-10 11:05:15 +0100 |
---|---|---|
committer | Tibor Frank <tifrank@cisco.com> | 2019-05-10 10:32:35 +0000 |
commit | b4b1c9bf381c1570a15651dfb1997a657cbbcc92 (patch) | |
tree | 023625467d35aa1d9097d3dbaa0154582fe8324a /docs/report/introduction/methodology_data_plane_throughput | |
parent | e79a1eed9da5aa88e783d442743025b3fc73ba77 (diff) |
report: edits of methodology mlrsearch section
Change-Id: I80b4f8223d2991e258ab422c447bdc09d92c9e9c
Signed-off-by: Maciek Konstantynowicz <mkonstan@cisco.com>
Diffstat (limited to 'docs/report/introduction/methodology_data_plane_throughput')
2 files changed, 29 insertions, 265 deletions
diff --git a/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst b/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst index 762a7c2675..3d33b22b55 100644 --- a/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst +++ b/docs/report/introduction/methodology_data_plane_throughput/methodology_data_plane_throughput.rst @@ -22,10 +22,10 @@ Description Multiple Loss Ratio search (MLRsearch) tests discover multiple packet throughput rates in a single search, reducing the overall test execution -time compared to a binary search. Each rate associated with a distinct -Packet Loss Ratio (PLR) criteria. In FD.io CSIT two throughput rates are -discovered: Non-Drop Rate (NDR, with zero packet loss, PLR=0) and -Partial Drop Rate (PDR, with PLR<0.5%). MLRsearch is compliant with +time compared to a binary search. Each rate is associated with a +distinct Packet Loss Ratio (PLR) criteria. In FD.io CSIT two throughput +rates are discovered: Non-Drop Rate (NDR, with zero packet loss, PLR=0) +and Partial Drop Rate (PDR, with PLR<0.5%). MLRsearch is compliant with :rfc:`2544`. Usage diff --git a/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst b/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst index 6c2adfcd06..acc974841d 100644 --- a/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst +++ b/docs/report/introduction/methodology_data_plane_throughput/methodology_mlrsearch_tests.rst @@ -3,287 +3,51 @@ MLRsearch Tests --------------- +Overview +~~~~~~~~ + Multiple Loss Rate search (MLRsearch) tests use new search algorithm implemented in FD.io CSIT project. MLRsearch discovers multiple packet throughput rates in a single search, with each rate associated with a -distinct Packet Loss Ratio (PLR) criteria. MLRsearch is being -standardized in IETF with `draft-vpolak-mkonstan-mlrsearch-XX -<https://tools.ietf.org/html/draft-vpolak-mkonstan-mlrsearch-00>`_. +different Packet Loss Ratio (PLR) criteria. Two throughput measurements used 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). MLRsearch -discovers NDR and PDR in a single pass reducing required execution time -compared to separate binary searches for NDR and PDR. MLRsearch reduces -execution time 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 search -execution time when compared to a standard NDR/PDR binary search, -while guaranteeing the same or similar results. +loss rate not greater than the configured non-zero PLR). -If needed, MLRsearch can be easily adopted to discover more throughput rates -with different pre-defined PLRs. +MLRsearch discovers NDR and PDR in a single pass reducing required time +duration compared to separate binary searches for NDR and PDR. 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. + +If needed, MLRsearch can be easily adopted to discover more throughput +rates with different pre-defined PLRs. .. 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. -Overview -~~~~~~~~ - -The main properties of MLRsearch: - -- MLRsearch is a duration aware multi-phase multi-rate search algorithm. - - - Initial phase determines promising starting interval for the search. - - Intermediate phases progress towards defined final search criteria. - - Final phase executes measurements according to the final search - criteria. - -- *Initial phase*: - - - Uses link rate as a starting transmit rate and discovers the Maximum - Receive Rate (MRR) used as an input to the first intermediate phase. - -- *Intermediate phases*: - - - Start with initial trial duration (in the first phase) and converge - geometrically towards the final trial duration (in the final phase). - - Track two values for NDR and two for PDR. - - - The values are called (NDR or PDR) lower_bound and upper_bound. - - Each value comes from a specific trial measurement - (most recent for that transmit rate), - and as such the value is associated with that measurement's duration and - loss. - - A bound can be invalid, for example if NDR lower_bound - has been measured with nonzero loss. - - Invalid bounds are not real boundaries for the searched value, - but are needed to track interval widths. - - Valid bounds are real boundaries for the searched value. - - Each non-initial phase ends with all bounds valid. - - - Start with a large (lower_bound, upper_bound) interval width and - geometrically converge towards the width goal (measurement resolution) - of the phase. Each phase halves the previous width goal. - - Use internal and external searches: - - - External search - measures at transmit rates outside the (lower_bound, - upper_bound) interval. Activated when a bound is invalid, - to search for a new valid bound by doubling the interval width. - It is a variant of `exponential search`_. - - Internal search - `binary search`_, measures at transmit rates within the - (lower_bound, upper_bound) valid interval, halving the interval width. - -- *Final phase* is executed with the final test trial duration, and the final - width goal that determines resolution of the overall search. - Intermediate phases together with the final phase are called non-initial - phases. - -The main benefits of MLRsearch vs. binary search include: - -- In general MLRsearch is likely to execute more search trials overall, but - less trials at a set final duration. -- In well behaving cases it greatly reduces (>50%) the overall duration - compared to a single PDR (or NDR) binary search duration, - while finding multiple drop rates. -- In all cases MLRsearch yields the same or similar results to binary search. -- Note: both binary search and MLRsearch are susceptible to reporting - non-repeatable results across multiple runs for very bad behaving - cases. - -Caveats: - -- Worst case MLRsearch can take longer than a binary search e.g. in case of - drastic changes in behaviour for trials at varying durations. - Search Implementation ~~~~~~~~~~~~~~~~~~~~~ -Following is a brief description of the current MLRsearch -implementation in FD.io CSIT. - -Input Parameters -```````````````` - -#. *maximum_transmit_rate* - maximum packet transmit rate to be used by - external traffic generator, limited by either the actual Ethernet - link rate or traffic generator NIC model capabilities. Sample - defaults: 2 * 14.88 Mpps for 64B 10GE link rate, - 2 * 18.75 Mpps for 64B 40GE NIC maximum rate. -#. *minimum_transmit_rate* - minimum packet transmit rate to be used for - measurements. MLRsearch fails if lower transmit rate needs to be - used to meet search criteria. Default: 2 * 10 kpps (could be higher). -#. *final_trial_duration* - required trial duration for final rate - measurements. Default: 30 sec. -#. *initial_trial_duration* - trial duration for initial MLRsearch phase. - Default: 1 sec. -#. *final_relative_width* - required measurement resolution expressed as - (lower_bound, upper_bound) interval width relative to upper_bound. - Default: 0.5%. -#. *packet_loss_ratio* - maximum acceptable PLR search criteria for - PDR measurements. Default: 0.5%. -#. *number_of_intermediate_phases* - number of phases between the initial - phase and the final phase. Impacts the overall MLRsearch duration. - Less phases are required for well behaving cases, more phases - may be needed to reduce the overall search duration for worse behaving - cases. - Default (2). (Value chosen based on limited experimentation to date. - More experimentation needed to arrive to clearer guidelines.) - -Initial Phase -````````````` - -1. First trial measures at maximum rate and discovers MRR. - - a. *in*: trial_duration = initial_trial_duration. - b. *in*: offered_transmit_rate = maximum_transmit_rate. - c. *do*: single trial. - d. *out*: measured loss ratio. - e. *out*: mrr = measured receive rate. - -2. Second trial measures at MRR and discovers MRR2. - - a. *in*: trial_duration = initial_trial_duration. - b. *in*: offered_transmit_rate = MRR. - c. *do*: single trial. - d. *out*: measured loss ratio. - e. *out*: mrr2 = measured receive rate. - -3. Third trial measures at MRR2. +Detailed description of the MLRsearch algorithm is included in the IETF +draft `draft-vpolak-mkonstan-mlrsearch +<https://tools.ietf.org/html/draft-vpolak-mkonstan-bmwg-mlrsearch>`_ +that is in the process of being standardized in the IETF Benchmarking +Methodology Working Group (BMWG). - a. *in*: trial_duration = initial_trial_duration. - b. *in*: offered_transmit_rate = MRR2. - c. *do*: single trial. - d. *out*: measured loss ratio. - -Non-initial Phases -`````````````````` - -1. Main loop: - - a. *in*: trial_duration for the current phase. - Set to initial_trial_duration for the first intermediate phase; - to final_trial_duration for the final phase; - or to the element of interpolating geometric sequence - for other intermediate phases. - For example with two intermediate phases, trial_duration - of the second intermediate phase is the geometric average - of initial_strial_duration and final_trial_duration. - b. *in*: relative_width_goal for the current phase. - Set to final_relative_width for the final phase; - doubled for each preceding phase. - For example with two intermediate phases, - the first intermediate phase uses quadruple of final_relative_width - and the second intermediate phase uses double of final_relative_width. - c. *in*: ndr_interval, pdr_interval from the previous main loop iteration - or the previous phase. - If the previous phase is the initial phase, both intervals have - lower_bound = MRR2, uper_bound = MRR. - Note that the initial phase is likely to create intervals with invalid - bounds. - d. *do*: According to the procedure described in point 2, - either exit the phase (by jumping to 1.g.), - or prepare new transmit rate to measure with. - e. *do*: Perform the trial measurement at the new transmit rate - and trial_duration, compute its loss ratio. - f. *do*: Update the bounds of both intervals, based on the new measurement. - The actual update rules are numerous, as NDR external search - can affect PDR interval and vice versa, but the result - agrees with rules of both internal and external search. - For example, any new measurement below an invalid lower_bound - becomes the new lower_bound, while the old measurement - (previously acting as the invalid lower_bound) - becomes a new and valid upper_bound. - Go to next iteration (1.c.), taking the updated intervals as new input. - g. *out*: current ndr_interval and pdr_interval. - In the final phase this is also considered - to be the result of the whole search. - For other phases, the next phase loop is started - with the current results as an input. - -2. New transmit rate (or exit) calculation (for 1.d.): - - - If there is an invalid bound then prepare for external search: - - - *If* the most recent measurement at NDR lower_bound transmit rate - had the loss higher than zero, then - the new transmit rate is NDR lower_bound - decreased by two NDR interval widths. - - Else, *if* the most recent measurement at PDR lower_bound - transmit rate had the loss higher than PLR, then - the new transmit rate is PDR lower_bound - decreased by two PDR interval widths. - - Else, *if* the most recent measurement at NDR upper_bound - transmit rate had no loss, then - the new transmit rate is NDR upper_bound - increased by two NDR interval widths. - - Else, *if* the most recent measurement at PDR upper_bound - transmit rate had the loss lower or equal to PLR, then - the new transmit rate is PDR upper_bound - increased by two PDR interval widths. - - If interval width is higher than the current phase goal: - - - Else, *if* NDR interval does not meet the current phase width goal, - prepare for internal search. The new transmit rate is - (NDR lower bound + NDR upper bound) / 2. - - Else, *if* PDR interval does not meet the current phase width goal, - prepare for internal search. The new transmit rate is - (PDR lower bound + PDR upper bound) / 2. - - Else, *if* some bound has still only been measured at a lower duration, - prepare to re-measure at the current duration (and the same transmit - rate). The order of priorities is: - - - NDR lower_bound, - - PDR lower_bound, - - NDR upper_bound, - - PDR upper_bound. - - *Else*, do not prepare any new rate, to exit the phase. - This ensures that at the end of each non-initial phase - all intervals are valid, narrow enough, and measured - at current phase trial duration. +MLRsearch is also available as a `PyPI (Python Package Index) library +<https://pypi.org/project/MLRsearch/>`_. Implementation Deviations ~~~~~~~~~~~~~~~~~~~~~~~~~ -This document so far has been describing a simplified version of MLRsearch -algorithm. The full algorithm as implemented contains additional logic, -which makes some of the details (but not general ideas) above incorrect. -Here is a short description of the additional logic as a list of principles, -explaining their main differences from (or additions to) the simplified -description,but without detailing their mutual interaction. - -1. *Logarithmic transmit rate.* - In order to better fit the relative width goal, - the interval doubling and halving is done differently. - For example, the middle of 2 and 8 is 4, not 5. -2. *Optimistic maximum rate.* - The increased rate is never higher than the maximum rate. - Upper bound at that rate is always considered valid. -3. *Pessimistic minimum rate.* - The decreased rate is never lower than the minimum rate. - If a lower bound at that rate is invalid, - a phase stops refining the interval further (until it gets re-measured). -4. *Conservative interval updates.* - Measurements above current upper bound never update a valid upper bound, - even if drop ratio is low. - Measurements below current lower bound always update any lower bound - if drop ratio is high. -5. *Ensure sufficient interval width.* - Narrow intervals make external search take more time to find a valid bound. - If the new transmit increased or decreased rate would result in width - less than the current goal, increase/decrease more. - This can happen if the measurement for the other interval - makes the current interval too narrow. - Similarly, take care the measurements in the initial phase - create wide enough interval. -6. *Timeout for bad cases.* - The worst case for MLRsearch is when each phase converges to intervals - way different than the results of the previous phase. - Rather than suffer total search time several times larger - than pure binary search, the implemented tests fail themselves - when the search takes too long (given by argument *timeout*). +FD.io CSIT implementation of MLRsearch so far is fully based on the -01 +version of the `draft-vpolak-mkonstan-mlrsearch-01 +<https://tools.ietf.org/html/draft-vpolak-mkonstan-bmwg-mlrsearch-01>`_. .. _binary search: https://en.wikipedia.org/wiki/Binary_search .. _exponential search: https://en.wikipedia.org/wiki/Exponential_search |