Re: [Cerowrt-devel] SQM Question #5: Link Layer Adaptation Overheads

[Sebastian Moeller <moeller0@gmx.de>]

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Hi David,


On Jan 7, 2014, at 13:11 , David Personette <dperson@gmail.com> wrote:

> I was going to test the recommended bridge settings for overhead (32 IIRC), because as far as I can tell there is no PPPoE involved. I've never seen it in the modems config (in the brief period it has an IP before I put it in bridge mode as well so the routable IP goes to my actual router), or needed to configure it on my router.

	Ah, so there are 2 major variations of "bridged":
1) 	LLC/SNAP: 	Bridged - 32 (ATM - 18, ethernet 14, possibly FCS - 4+padding)
2)	VC-MUX:	Bridged - 24 (ATM - 10, ethernet 14, possibly FCS - 4+padding)
(he FCS padding potentially turns this into 4 variations, but it should be really rare, or so I heard).

	You could just slowly reduce the overhead and see how the link behaves; honestly I do not know how prominent a slight overhead underestimate would feel, so by all means go ahead and try :). If you have a mac or linux computer on your network, you could try to measure the overhead with the attached ping_sweeper5_dp.sh script (needs editing). Then you could run tc_stab_parameter_guide_04.m in matlab or octave (on the matlab command prompt change into the directory containing the script and the log file run "[ tmp ] = tc_stab_parameter_guide_04( fullfile(pwd, 'ping_sweep_ADSL2_20140104_122844.txt'))" ; make sure to replace ping_sweep_ADSL2_20140104_122844.txt with the name of your log file. The measurement will take around 3 hours (for 10000 samples per size, for your link 1000 would be enough) and wants an undisturbed network (I typically run this over night); the parsing of the log file will also consume 20 minutes or more, the actual analysis will take a few seconds…
	If you go that route I would love it if you could share your log file, since I only have one old bridged LLC/SNAP example. (I intend to put all scripts and an instruction on the wiki, with example plots for the different results).


Best Regards
	Sebastian

[-- Attachment #2: tc_stab_parameter_guide_04.m --]
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function [ output_args ] = tc_stab_parameter_guide_04( sweep_fqn, up_Kbit, down_Kbit )
%TC_STAB_PARAMETER_GUIDE Summary of this function goes here
%   try to read in the result from a ping sweep run
%	sweep_fqn: the log file of the ping sweep against the first hop after
%		the DSL link
%	up_Kbit: the uplink rate in Kilobits per second
%	down_Kbit: the downlink rate in Kilobits per second
%
% TODO:
%	find whether the carrier is ATM quantized (via FFT?)
%		test whther best stair fits better than a simple linear regresson
%		line?
%	if yes:
%		what is the RTT step (try to deduce the combined up and down rates from this)
%	estimate the best MTU for the estimated protocol stack (how to test this?)
%		1) estimate the largest MTU that avoids fragmentation (default 1500 - 28 should be largest without fragmentation)
%		2) estimate the largest MTU that does not have padding in the last
%		   ATM cell, for this pick the MTU that no partial ATM cell remains
%	implement robust mean (mean between certain quantiles), does that make
%	sense with RTT distribution?
%
% DONE:
%	Allow for holes in the ping data (missing sizes)
%	make sure all sizes are filled (use NaN for empty ones?)
%	maybe require to give the nominal up and down rates, to estimate the
%		RTT stepsize
%	try to figure out the overhead for each packet
%
%Thoughts:
%	ask about IPv4 or IPv6 (what about tunnelling?)
%	the sweep should be taken directly connected to the modem to reduce
%		non-ATM routing delays

dbstop if error;
if ~(isoctave)
	timestamps.(mfilename).start = tic;
else
	tic();
end
disp(['Starting: ', mfilename]);

output_args = [];

% control options
show_mean = 1;		% the means are noisier than the medians
show_robust_mean = 1;		% the means are noisier than the medians
show_median = 1;	% the median seems the way to go
show_min = 1;		% the min should be the best measure, but in the ATM test sweep it is too variable
show_max = 0;		% only useful for debugging
show_sem = 0;		% give some estimate of the variance
show_ci = 1;		% show the confidence interval of the mean, if the mean is shown
ci_alpha = 0.05;	% alpha for confidence interval calculation
use_measure = 'median';
use_processed_results = 1;
max_samples_per_size = [];	% if not empty only use maximally that many samples per size


% if not specified we try to estimate the per cell RTT from the data
default_up_Kbit = [];
default_down_KBit = [];

if (nargin == 0)
	sweep_fqn = '';
	sweep_fqn = fullfile(pwd, 'ping_sweep_ATM.txt');	% was Bridged, LLC/SNAP RFC-1483/2684 connection (overhead 32 bytes - 14 = 18)
	sweep_fqn = fullfile(pwd, 'ping_sweep_ATM_20130610_234707.txt');	% telekom PPPOE, LLC, overhead 40!
	sweep_fqn = fullfile(pwd, 'ping_sweep_ATM_20130618_233008.txt');	% telekom PPPOE
	sweep_fqn = fullfile(pwd, 'ping_sweep_ATM_20130620_234659.txt');	% telekom PPPOE
	sweep_fqn = fullfile(pwd, 'ping_sweep_ATM_20130618-20.txt');	% telekom PPPOE
	%  	sweep_fqn = fullfile(pwd, 'ping_sweep_CABLE_20120426_230227.txt');
	%  	sweep_fqn = fullfile(pwd, 'ping_sweep_CABLE_20120801_001235.txt');
	if isempty(sweep_fqn)
		[sweep_name, sweep_dir] = uigetfile('ping*.txt');
		sweep_fqn = fullfile(sweep_dir, sweep_name);
	end
	up_Kbit = default_up_Kbit;
	down_Kbit = default_down_KBit;
end
if (nargin == 1)
	up_Kbit = default_up_Kbit;
	down_Kbit = default_down_KBit;
end
if (nargin == 2)
	down_Kbit = default_down_KBit;
end

%ATM
quantum.byte = 48;	% ATM packets are always 53 bytes, 48 thereof payload
quantum.bit = quantum.byte * 8;
ATM_cell.byte = 53;
ATM_cell.bit = ATM_cell.byte * 8;


% known packet size offsets in bytes
offsets.IPv4 = 20;		% assume no IPv4 options are used, IPv6 would be 40bytes?
offsets.IPv6 = 40;		% not used yet...
offsets.ICMP = 8;		% ICMP header
offsets.ethernet = 14;	% ethernet header
offset.ATM.max_encapsulation_bytes = 44; % see http://ace-host.stuart.id.au/russell/files/tc/tc-atm/
MTU = 1500;	% the nominal MTU to the ping host should be 1500, but might be lower if using a VPN
% fragmentation will cause an addition relative large increase in RTT (not necessarily registered to the ATM cells)
% that will confuse the ATM quantisation offset detector, so exclude all
% ping sizes that are potentially affected by fragmentation
max_ping_size_without_fragmentation = MTU + offsets.ethernet - offsets.IPv4 - offset.ATM.max_encapsulation_bytes; 
% unknown offsets is what we need to figure out to feed tc-stab...


[sweep_dir, sweep_name] = fileparts(sweep_fqn);
cur_parsed_data_mat = [sweep_fqn(1:end-4), '.mat'];

if (use_processed_results && ~isempty(dir(cur_parsed_data_mat)))
	disp(['Loading processed ping data from ', cur_parsed_data_mat]);
	load(cur_parsed_data_mat, 'ping');
else
	% read in the result from a ping sweep
	disp(['Processing ping data from ', sweep_fqn]);
	ping = parse_ping_output(sweep_fqn);
	if isempty(ping)
		disp('No useable ping data found, exiting...');
		return
	end
	save(cur_parsed_data_mat, 'ping');
end




% analyze the data
min_ping_size = min(ping.data(:, ping.cols.size)) - offsets.ICMP;
disp(['Minimum size of ping payload used: ', num2str(min_ping_size), ' bytes.']);
known_overhead = offsets.IPv4;	% ping reports the ICMP header already included in size
ping.data(:, ping.cols.size) = ping.data(:, ping.cols.size) + known_overhead;	% we know we used IPv4 so add the 20 bytes already, so that size are relative to the start of the IP header
size_list = unique(ping.data(:, ping.cols.size));	% this is the number of different sizes, but there might be holes/missing sizes
max_pingsize = max(size_list);

per_size.header = {'size', 'mean', 'robust_mean', 'median', 'min', 'max', 'std', 'n', 'sem', 'ci'};
per_size.cols = get_column_name_indices(per_size.header);
per_size.data = zeros([max_pingsize, length(per_size.header)]) / 0;	% NaNs
per_size.data(:, per_size.cols.size) = (1:1:max_pingsize);

if ~isempty(max_samples_per_size)
	disp(['Analysing only the first ', num2str(max_samples_per_size), ' samples.']);
end

for i_size = 1 : length(size_list)
	cur_size = size_list(i_size);
	cur_size_idx = find(ping.data(:, ping.cols.size) == cur_size);
	if ~isempty(max_samples_per_size)
		n_selected_samples = min([length(cur_size_idx), max_samples_per_size]);
		cur_size_idx = cur_size_idx(1:n_selected_samples);
		%disp(['Analysing only the first ', num2str(max_samples_per_size), ' samples of ', num2str(length(cur_size_idx))]);
	end	
	per_size.data(cur_size, per_size.cols.mean) = mean(ping.data(cur_size_idx, ping.cols.time));
	% robust mean, aka mean of 5 to 95 quantiles
	per_size.data(cur_size, per_size.cols.robust_mean) = robust_mean(ping.data(cur_size_idx, ping.cols.time), 0.1, 0.9);	% take the mean while excluding extreme values
	
	per_size.data(cur_size, per_size.cols.median) = median(ping.data(cur_size_idx, ping.cols.time));
	per_size.data(cur_size, per_size.cols.min) = min(ping.data(cur_size_idx, ping.cols.time));
	per_size.data(cur_size, per_size.cols.max) = max(ping.data(cur_size_idx, ping.cols.time));
	per_size.data(cur_size, per_size.cols.std) = std(ping.data(cur_size_idx, ping.cols.time), 0);
	per_size.data(cur_size, per_size.cols.n) = length(cur_size_idx);
	per_size.data(cur_size, per_size.cols.sem) = per_size.data(cur_size, per_size.cols.std) / sqrt(length(cur_size_idx));
	per_size.data(cur_size, per_size.cols.ci) = calc_cihw(per_size.data(cur_size, per_size.cols.std), per_size.data(cur_size, per_size.cols.n), ci_alpha);
end

clear ping	% with large data sets 32bit matlab will run into memory issues...


figure('Name', sweep_name);
hold on;
legend_str = {};
if (show_mean)
	% means
	legend_str{end + 1} = 'mean';
	plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.mean), 'Color', [0 1 0 ]);
	legend_str{end + 1} = 'robust mean';
	plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.robust_mean), 'Color', [0 0.75 0 ]);
	if  (show_sem)
		legend_str{end + 1} = '+sem';
		legend_str{end + 1} = '-sem';
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.mean) - per_size.data(:, per_size.cols.sem), 'Color', [0 0.66 0]);
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.mean) + per_size.data(:, per_size.cols.sem), 'Color', [0 0.66 0]);
	end
	if  (show_ci)
		legend_str{end + 1} = '+ci';
		legend_str{end + 1} = '-ci';
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.mean) - per_size.data(:, per_size.cols.ci), 'Color', [0 0.37 0]);
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.mean) + per_size.data(:, per_size.cols.ci), 'Color', [0 0.37 0]);
	end
	
end
if(show_median)
	% median +- standard error of the mean, confidence interval would be
	% better
	legend_str{end + 1} = 'median';
	plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.median), 'Color', [1 0 0]);
	if (show_sem)
		legend_str{end + 1} = '+sem';
		legend_str{end + 1} = '-sem';
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.median) - per_size.data(:, per_size.cols.sem), 'Color', [0.66 0 0]);
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.median) + per_size.data(:, per_size.cols.sem), 'Color', [0.66 0 0]);
	end
	if(show_min)
		% minimum, should be cleanest, but for the test data set looks quite sad...
		legend_str{end + 1} = 'min';
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.min), 'Color', [0 0 1]);
	end
	if(show_max)
		% minimum, should be cleanest, but for the test data set looks quite sad...
		legend_str{end + 1} = 'max';
		plot(per_size.data(:, per_size.cols.size), per_size.data(:, per_size.cols.max), 'Color', [0 0 0.66]);
	end
end

title(['If this plot shows a (noisy) step function with a stepping ~', num2str(quantum.byte), ' bytes then the data carrier is quantised, make sure to use tc-stab']);
xlabel('Approximate packet size [bytes]');
ylabel('ICMP round trip times (ping RTT) [ms]');
legend(legend_str, 'Location', 'NorthWest');
hold off;

% potentially clean up the data, by interpolating values with large sem
% from the neighbours or replacing those with NaNs?

% if the size of the ping packet exceeds the MTU the ping packets gets
% fragmented the step over this ping size will cause a RTT increaser >> one
% RTT_quantum, so exclude all sizes potentially affected by this from the
% search space, (for now assume that the route to the ping host actually can carry 1500 byte MTUs...)
measured_pingsize_idx = find(~isnan(per_size.data(:, per_size.cols.(use_measure))));
tmp_idx = find(measured_pingsize_idx <= max_ping_size_without_fragmentation);
last_non_fragmented_pingsize = measured_pingsize_idx(tmp_idx(end));
ping_sizes_for_linear_fit = measured_pingsize_idx(tmp_idx);

% fit a line to the data, to estimate the RTT per byte
[p, S] = polyfit(per_size.data(ping_sizes_for_linear_fit, per_size.cols.size), per_size.data(ping_sizes_for_linear_fit, per_size.cols.(use_measure)), 1);
RTT_per_byte = p(end - 1);
fitted_line = polyval(p, per_size.data(ping_sizes_for_linear_fit, per_size.cols.size), S);
input_data = per_size.data(ping_sizes_for_linear_fit, per_size.cols.(use_measure));
% estimate the goodness of the linear fit the same way as for the stair
% function
linear_cumulative_difference = sum(abs(input_data - fitted_line));

% figure
% hold on
% plot(per_size.data(ping_sizes_for_linear_fit, per_size.cols.size), per_size.data(ping_sizes_for_linear_fit, per_size.cols.(use_measure)), 'Color', [0 1 0]);
% plot(per_size.data(ping_sizes_for_linear_fit, per_size.cols.size), fitted_line, 'Color', [1 0 0]);
% hold off
% based on the linear fit we can estimate the average RTT per ATM cell
estimated_RTT_quantum_ms = RTT_per_byte * 48;


% the RTT should equal the average RTT increase per ATM quantum
% estimate the RTT step size
% at ADSL down 3008kbit/sec up 512kbit/sec we expect, this does not include
% processing time
if ~isempty(down_Kbit) || ~isempty(up_Kbit)
	expected_RTT_quantum_ms = (ATM_cell.bit / (down_Kbit * 1024) + ATM_cell.bit / (up_Kbit * 1024) ) * 1000;	% this estimate is rather a lower bound for fastpath , so search for best fits
else
	expected_RTT_quantum_ms = estimated_RTT_quantum_ms;
end
disp(['lower bound estimate for one ATM cell RTT based of specified up and downlink is ', num2str(expected_RTT_quantum_ms), ' ms.']);
disp(['estimate for one ATM cell RTT based on linear fit of the ping sweep data is ', num2str(estimated_RTT_quantum_ms), ' ms.']);

% lets search from expected_RTT_quantum_ms to 1.5 * expected_RTT_quantum_ms
% in steps of expected_RTT_quantum_ms / 100
% to allow for interleaved ATM set ups increase the search space up to 32
% times best fastpath RTT estimate, 64 interleave seems to add 25ms to the
% latency, but this only 
RTT_quantum_list = (expected_RTT_quantum_ms / 2 : expected_RTT_quantum_ms / 100 : 32 * expected_RTT_quantum_ms);
quantum_list = (1 : 1 : quantum.byte);

% BRUTE FORCE search of best fitting stair...
differences = zeros([length(RTT_quantum_list) length(quantum_list)]);
cumulative_differences = differences;


all_stairs = zeros([length(RTT_quantum_list) length(quantum_list) length(per_size.data(1:last_non_fragmented_pingsize, per_size.cols.(use_measure)))]);
for i_RTT_quant = 1 : length(RTT_quantum_list)
	cur_RTT_quant = RTT_quantum_list(i_RTT_quant);
	for i_quant = 1 : quantum.byte
		[differences(i_RTT_quant, i_quant), cumulative_differences(i_RTT_quant, i_quant), all_stairs(i_RTT_quant, i_quant, :)] = ...
			get_difference_between_data_and_stair( per_size.data(1:last_non_fragmented_pingsize, per_size.cols.size), per_size.data(1:last_non_fragmented_pingsize, per_size.cols.(use_measure)), ...
			quantum_list(i_quant), quantum.byte, 0, cur_RTT_quant );
	end
end

% for the initial test DSL set the best x_offset was 21, corresponding to 32 bytes overhead before the IP header.
[min_cum_diff, min_cum_diff_idx] = min(cumulative_differences(:));
[min_cum_diff_row_idx, min_cum_diff_col_idx] = ind2sub(size(cumulative_differences),min_cum_diff_idx);
best_difference = differences(min_cum_diff_row_idx, min_cum_diff_col_idx);
disp(['Best staircase fit cumulative difference is: ', num2str(cumulative_differences(min_cum_diff_row_idx, min_cum_diff_col_idx))]);
disp(['Best linear fit cumulative difference is: ', num2str(linear_cumulative_difference)]);
% judge the quantization
if (cumulative_differences(min_cum_diff_row_idx, min_cum_diff_col_idx) < linear_cumulative_difference)
	% stair fits better than line
	quant_string = ['Quantized ATM carrier LIKELY (cummulative residual: stair fit ', num2str(cumulative_differences(min_cum_diff_row_idx, min_cum_diff_col_idx)), ' linear fit ', num2str(linear_cumulative_difference)];
else
	quant_string = ['Quantized ATM carrier UNLIKELY (cummulative residual: stair fit ', num2str(cumulative_differences(min_cum_diff_row_idx, min_cum_diff_col_idx)), ' linear fit ', num2str(linear_cumulative_difference)];	
end
disp(quant_string);

disp(['remaining ATM cell length after ICMP header is ', num2str(quantum_list(min_cum_diff_col_idx)), ' bytes.']);
disp(['ICMP RTT of a single ATM cell is ', num2str(RTT_quantum_list(min_cum_diff_col_idx)), ' ms.']);


% as first approximation use the ATM cell offset and known offsets (ICMP
% IPv4 min_ping_size) to estimate the number of cells used for per packet
% overhead
% this assumes that no ATM related overhead is >= ATM cell size
% -1 to account for matlab 1 based indices
% what is the offset in the 2nd ATM cell
n_bytes_overhead_2nd_cell = quantum.byte - (quantum_list(min_cum_diff_col_idx) - 1);	% just assume we can not fit all overhead into one cell...
% what is the known overhead size for the first data point:
tmp_idx = find(~isnan(per_size.data(:, per_size.cols.mean)));
known_overhead_first_ping_size = tmp_idx(1);
%pre_IP_overhead = quantum.byte + (n_bytes_overhead_2nd_cell - known_overhead);	% ths is the one we are after in the end
pre_IP_overhead = quantum.byte + (n_bytes_overhead_2nd_cell - known_overhead_first_ping_size);	% ths is the one we are after in the end
disp(' ');
disp(['Estimated overhead preceding the IP header: ', num2str(pre_IP_overhead), ' bytes']);


figure('Name', 'Comparing ping data with');
hold on
legend_str = {'ping_data', 'fitted_stair', 'fitted_line'};
plot(per_size.data(1:last_non_fragmented_pingsize, per_size.cols.size), per_size.data(1:last_non_fragmented_pingsize, per_size.cols.(use_measure)), 'Color', [1 0 0]);
plot(per_size.data(1:last_non_fragmented_pingsize, per_size.cols.size), squeeze(all_stairs(min_cum_diff_row_idx, min_cum_diff_col_idx, :)) + best_difference, 'Color', [0 1 0]);

fitted_line = polyval(p, per_size.data(1:last_non_fragmented_pingsize, per_size.cols.size), S);
plot(per_size.data(1:last_non_fragmented_pingsize, per_size.cols.size), fitted_line, 'Color', [0 0 1]);

title({['Estimated RTT per quantum: ', num2str(RTT_quantum_list(min_cum_diff_col_idx)), ' ms; ICMP data offset in quantum ', num2str(quantum_list(min_cum_diff_col_idx)), ' bytes'];...
	['Estimated overhead preceding the IP header: ', num2str(pre_IP_overhead), ' bytes'];...
	quant_string});
xlabel('Approximate packet size [bytes]');
ylabel('ICMP round trip times (ping RTT) [ms]');
if (isoctave)
	legend(legend_str, 'Location', 'NorthWest');
else
	%annotation('textbox', [0.0 0.95 1.0 .05], 'String', ['Estimated overhead preceding the IP header: ', num2str(pre_IP_overhead), ' bytes'], 'FontSize', 9, 'Interpreter', 'none', 'Color', [1 0 0], 'LineStyle', 'none');
	legend(legend_str, 'Interpreter', 'none', 'Location', 'NorthWest');
end
hold off



% use http://ace-host.stuart.id.au/russell/files/tc/tc-atm/ to present the
% most likely ATM encapsulation for a given overhead and present a recommendation
% for the tc stab invocation
display_protocol_stack_information(pre_IP_overhead);


% now turn this into tc-stab recommendations:
disp(['Add the following to both the egress root qdisc:']);
% disp(' ');
disp(['A) Assuming the router connects over ethernet to the DSL-modem:']);
disp(['stab mtu 2048 tsize 128 overhead ', num2str(pre_IP_overhead), ' linklayer atm']);	% currently tc stab does not account for the ethernet header
% disp(['stab mtu 2048 tsize 128 overhead ', num2str(pre_IP_overhead - offsets.ethernet), ' linklayer atm']);
% disp(' ');
% disp(['B) Assuming the router connects via PPP and non-ethernet to the modem:']);
% disp(['stab mtu 2048 tsize 128 overhead ', num2str(pre_IP_overhead), ' linklayer atm']);

disp(' ');
% on ingress do not exclude the the ethernet header?
disp(['Add the following to both the ingress root qdisc:']);
disp(' ');
disp(['A) Assuming the router connects over ethernet to the DSL-modem:']);
disp(['stab mtu 2048 tsize 128 overhead ', num2str(pre_IP_overhead), ' linklayer atm']);
disp(' ');
if ~(isoctave)
	timestamps.(mfilename).end = toc(timestamps.(mfilename).start);
	disp([mfilename, ' took: ', num2str(timestamps.(mfilename).end), ' seconds.']);
else
	toc
end

% and now the other end of the data, what is the max MTU for the link and
% what is the best ATM cell aligned MTU

disp('Done...');

return
end


function [ ping_data ] = parse_ping_output( ping_log_fqn )
%PARSE_PING_OUTPUT read the putput of a ping run/sweep
% for further processing
% TODO:
%	use a faster parser, using srtok is quite expensive
%


if ~(isoctave)
	timestamps.parse_ping_output.start = tic;
else
	tic();
end

verbose = 0;
n_rows_to_grow_table_by = 10000;	% grow table increment to avoid excessive memory copy ops


ping_data = [];
cur_sweep_fd = fopen(ping_log_fqn, 'r');
if (cur_sweep_fd == -1)
	disp(['Could not open ', ping_log_fqn, '.']);
	if isempty(dir(ping_log_fqn))
		disp('Reason: file does not seem to exist at the given directory...')
	end
	return
end
ping_data.header = {'size', 'icmp_seq', 'ttl', 'time'};
ping_data.field_names_list = {'size', 'icmp_seq', 'seq', 'ttl', 'time'};

ping_data.header = {'size', 'time'};	% save half the size...
ping_data.field_names_list = {'size', 'time'};

ping_data.cols = get_column_name_indices(ping_data.header);

ping_data.data = zeros([n_rows_to_grow_table_by, length(ping_data.header)]);
cur_data_lines = 0;
cur_lines = 0;

% skip the first line
% PING netblock-75-79-143-1.dslextreme.com (75.79.143.1): (16 ... 1000)
% data bytes
header_line = fgetl(cur_sweep_fd);

while ~feof(cur_sweep_fd)
	% grow the data table if need be
	if (size(ping_data.data, 1) == cur_data_lines)
		if (verbose)
			disp('Growing ping data table...');
		end
		ping_data.data = [ping_data.data; zeros([n_rows_to_grow_table_by, length(ping_data.header)])];
	end
	
	cur_line = fgetl(cur_sweep_fd);
	if ~(mod(cur_lines, 1000))
		disp([num2str(cur_lines +1), ' lines parsed...']);
	end
	cur_lines = cur_lines + 1;
	
	[first_element, remainder] = strtok(cur_line);
	first_element_as_number = str2double(first_element);
	if isempty(first_element) || strcmp('Request', first_element) || strcmp('---', first_element)
		% skip empty lines explicitly
		continue;
	end
	% the following will not work for merged ping
	%if strmatch('---', first_element)
	%	%we reached the end of sweeps
	%	break;
	%end
	% now read in the data
	% 30 bytes from 75.79.143.1: icmp_seq=339 ttl=63 time=14.771 ms
	if ~isempty(first_element_as_number)
		% get the next element
		[tmp_next_item, tmp_remainder] = strtok(remainder);
		if strcmp(tmp_next_item, 'bytes')
			if ~(mod(cur_data_lines, 1000))
				disp(['Milestone ', num2str(cur_data_lines +1), ' ping packets reached...']);
			end
			cur_data_lines = cur_data_lines + 1;
			
			% size of the ICMP package
			ping_data.data(cur_data_lines, ping_data.cols.size) = first_element_as_number;
			% now process the remainder
			while ~isempty(remainder)
				[next_item, remainder] = strtok(remainder);
				equality_pos = strfind(next_item, '=');
				% data items are name+value pairs
				if ~isempty(equality_pos);
					cur_key = next_item(1: equality_pos - 1);
					cur_value = str2double(next_item(equality_pos + 1: end));
					if (ismember(cur_key, ping_data.field_names_list))
						switch cur_key
							% busybox ping and macosx ping return different key names
							case {'seq', 'icmp_seq'}
								ping_data.data(cur_data_lines, ping_data.cols.icmp_seq) = cur_value;
							case 'ttl'
								ping_data.data(cur_data_lines, ping_data.cols.ttl) = cur_value;
							case 'time'
								ping_data.data(cur_data_lines, ping_data.cols.time) = cur_value;
						end
					end
				end
			end
		else
			% skip this line
			if (verbose)
				disp(['Skipping: ', cur_line]);
			end
		end
	else
		if (verbose)
			disp(['Ping output: ', cur_line, ' not handled yet...']);
		end
	end
	
end

% remove empty lines
if (size(ping_data.data, 1) > cur_data_lines)
	ping_data.data = ping_data.data(1:cur_data_lines, :);
end

disp(['Found ', num2str(cur_data_lines), ' ping packets in ', ping_log_fqn]);
% clean up
fclose(cur_sweep_fd);

if ~(isoctave)
	timestamps.parse_ping_output.end = toc(timestamps.parse_ping_output.start);
	disp(['Parsing took: ', num2str(timestamps.parse_ping_output.end), ' seconds.']);
else
	toc
end

return
end


function [ difference , cumulative_difference, stair_y ] = get_difference_between_data_and_stair( data_x, data_y, x_size, stair_x_step_size, y_offset, stair_y_step_size )
% 130619sm: handle NaNs in data_y (marker for missing ping sizes)
% x_size is the flat part of the first stair, that is quantum minus the
% offset
% TODO: understand the offset issue and simplify this function
%		extrapolate the stair towards x = 0 again

debug = 0;
difference = [];

tmp_idx = find(~isnan(data_y));
x_start_val_idx = tmp_idx(1);
x_start_val = data_x(x_start_val_idx);
x_end_val = data_x(end);	% data_x is sorted...

% construct stair
stair_x = data_x;
proto_stair_y = zeros([x_end_val 1]);	% we need the final value in
% make sure the x_size values do not exceed the step size...
if (x_size > stair_x_step_size)
	if mod(x_size, stair_x_step_size) == 0
		x_size = stair_x_step_size;
	else
		x_size = mod(x_size, stair_x_step_size);
	end
end

%stair_y_step_idx = (x_start_val + x_size : stair_x_step_size : x_end_val);
%% we really want steps registered to x_start_val
%stair_y_step_idx = (mod(x_start_val, stair_x_step_size) + x_size : stair_x_step_size : x_end_val);
stair_y_step_idx = (mod(x_start_val + x_size, stair_x_step_size) : stair_x_step_size : x_end_val);
if stair_y_step_idx(1) == 0
	stair_y_step_idx(1) = [];
end

proto_stair_y(stair_y_step_idx) = stair_y_step_size;
stair_y = cumsum(proto_stair_y);
if (debug)
	figure
	hold on;
	title(['x offset used: ', num2str(x_size), ' with quantum ', num2str(stair_x_step_size)]);
	plot(data_x, data_y, 'Color', [0 1 0]);
	plot(stair_x, stair_y, 'Color', [1 0 0]);
	hold off;
end
% missing ping sizes are filled with NaNs, so skip those
notnan_idx = find(~isnan(data_y));
% estimate the best y_offset for the stair
difference = sum(abs(data_y(notnan_idx) - stair_y(notnan_idx))) / length(data_y(notnan_idx));
% calculate the cumulative difference between stair and data...
cumulative_difference = sum(abs(data_y(notnan_idx) - (stair_y(notnan_idx) + difference)));

return
end

% function [ stair ] = build_stair(x_vector, x_size, stair_x_step_size, y_offset, stair_y_step_size )
% stair = [];
%
% return
% end


function [columnnames_struct, n_fields] = get_column_name_indices(name_list)
% return a structure with each field for each member if the name_list cell
% array, giving the position in the name_list, then the columnnames_struct
% can serve as to address the columns, so the functions assitgning values
% to the columns do not have to care too much about the positions, and it
% becomes easy to add fields.
n_fields = length(name_list);
for i_col = 1 : length(name_list)
	cur_name = name_list{i_col};
	columnnames_struct.(cur_name) = i_col;
end
return
end




function [ci_halfwidth_vector] = calc_cihw(std_vector, n, alpha)
%calc_ci : calculate the half width of the confidence interval (for 1 - alpha)
%	the t_value lookup depends on alpha and the samplesize n; the relevant
%	calculation of the degree of freedom is performed inside calc_t_val.
%	ci_halfwidth = t_val(alpha, n-1) * std / sqrt(n)
%	Each groups CI ranges from mean - ci_halfwidth to mean - ci_halfwidth, so
%	the calling function has to perform this calculation...
%
% INPUTS:
%	std_vector: vector containing the standard deviations of all requested
%		groups
%	n: number of samples in each group, if the groups have different
%		samplesizes, specify each group's sample size in a vector
%	alpha: the desired maximal uncertainty/error in the range of [0, 1]
% OUTPUT:
%	ci_halfwidth_vector: vector containing the confidence intervals half width
%		for each group

% calc_t_val return one sided t-values, for the desired two sidedness one has
% to half the alpha for the table lookup
cur_alpha = alpha / 2;

% if n is scalar use same n for all elements of std_vec
if isscalar(n)
	t_ci = calc_t_val(cur_alpha, n);
	ci_halfwidth_vector = std_vector * t_ci / sqrt(n);
	% if n is a vector, prepare a matching vector of t_ci values
elseif isvector(n)
	t_ci_vector = n;
	% this is probably ugly, but calc_t_val only accepts scalars.
	for i_pos = 1 : length(n)
		t_ci_vector(i_pos) = calc_t_val(cur_alpha, n(i_pos));
	end
	ci_halfwidth_vector = std_vector .* t_ci_vector ./ sqrt(n);
end

return
end

%-----------------------------------------------------------------------------
function [t_val] = calc_t_val(alpha, n)
% the t value for the given alpha and n
% so call with the n of the sample, not with degres of freedom
% see http://mathworld.wolfram.com/Studentst-Distribution.html for formulas
% return values follow Bortz, Statistik fuer Sozialwissenschaftler, Springer
% 1999, table D page 775. That is it returns one sided t-values.
% primary author S. Moeller

% TODO:
%	sidedness of t-value???

% basic error checking
if nargin < 2
	error('alpha and n have to be specified...');
end

% probabilty of error
tmp_alpha = alpha ;%/ 2;
if (tmp_alpha < 0) || (tmp_alpha > 1)
	msgbox('alpha has to be taken from [0, 1]...');
	t_val = NaN;
	return
end
if tmp_alpha == 0
	t_val = -Inf;
	return
elseif tmp_alpha ==1
	t_val = Inf;
	return
end
% degree of freedom
df = n - 1;
if df < 1
	%msgbox('The n has to be >= 2 (=> df >= 1)...');
	% 	disp('The n has to be >= 2 (=> df >= 1)...');
	t_val = NaN;
	return
end


% only calculate each (alpha, df) combination once, store the results
persistent t_val_array;
% create the t_val_array
if ~iscell(t_val_array)
	t_val_array = {[NaN;NaN]};
end
% search for the (alpha, df) tupel, avoid calculation if already stored
if iscell(t_val_array)
	% cell array of 2d arrays containing alpha / t_val pairs
	if df <= length(t_val_array)
		% test whether the required alpha, t_val tupel exists
		if ~isempty(t_val_array{df})
			% search for alpha
			tmp_array = t_val_array{df};
			alpha_index = find(tmp_array(1,:) == tmp_alpha);
			if any(alpha_index)
				t_val = tmp_array(2, alpha_index);
				return
			end
		end
	else
		% grow t_val_array to length of n
		missing_cols = df - length(t_val_array);
		for i_missing_cols = 1: missing_cols
			t_val_array{end + 1} = [NaN;NaN];
		end
	end
end

% check the sign
cdf_sign = 1;
if (1 - tmp_alpha) == 0.5
	t_val = t_cdf;
elseif (1 - tmp_alpha) < 0.5 % the t-cdf is point symmetric around (0, 0.5)
	cdf_sign = -1;
	tmp_alpha = 1 - tmp_alpha; % this will be undone later
end

% init some variables
n_iterations = 0;
delta_t = 1;
last_alpha = 1;
higher_t = 50;
lower_t = 0;
% find a t-value pair around the desired alpha value
while norm_students_cdf(higher_t, df) < (1 - tmp_alpha);
	lower_t = higher_t;
	higher_t = higher_t * 2;
end

% search the t value for the given alpha...
while (n_iterations < 1000) && (abs(delta_t) >= 0.0001)
	n_iterations = n_iterations + 1;
	% get the test_t (TODO linear interpolation)
	% higher_alpha = norm_students_cdf(higher_t, df);
	% lower_alpha = norm_students_cdf(lower_t, df);
	test_t = lower_t + ((higher_t - lower_t) / 2);
	cur_alpha = norm_students_cdf(test_t, df);
	% just in case we hit the right t spot on...
	if cur_alpha == (1 - tmp_alpha)
		t_crit = test_t;
		break;
		% probably we have to search for the right t
	elseif cur_alpha < (1 - tmp_alpha)
		% test_t is the new lower_t
		lower_t = test_t;
		%higher_t = higher_t;	% this stays as is...
	elseif cur_alpha > (1 - tmp_alpha)
		%
		%lower_t = lower_t;	% this stays as is...
		higher_t = test_t;
	end
	delta_t = higher_t - lower_t;
	last_alpha = cur_alpha;
end
t_crit = test_t;

% set the return value, correct for negative t values
t_val = t_crit * cdf_sign;
if cdf_sign < 0
	tmp_alpha = 1 - tmp_alpha;
end

% store the alpha, n, t_val tupel in t_val_array
pos = size(t_val_array{df}, 2);
t_val_array{df}(1, (pos + 1)) = tmp_alpha;
t_val_array{df}(2, (pos + 1)) = t_val;

return
end

%-----------------------------------------------------------------------------
function [scaled_cdf] = norm_students_cdf(t, df)
% calculate the cdf of students distribution for a given degree of freedom df,
% and all given values of t, then normalize the result
% the extreme values depend on the values of df!!!

% get min and max by calculating values for extrem t-values (e.g. -10000000,
% 10000000)
extreme_cdf_vals = students_cdf([-10000000, 10000000], df);

tmp_cdf = students_cdf(t, df);

scaled_cdf =	(tmp_cdf - extreme_cdf_vals(1)) /...
	(extreme_cdf_vals(2) - extreme_cdf_vals(1));
return
end

%-----------------------------------------------------------------------------
function [cdf_value_array] = students_cdf(t_value_array, df)
%students_cdf: calc the cumulative density function for a t-distribution
% Calculate the CDF value for each value t of the input array
% see http://mathworld.wolfram.com/Studentst-Distribution.html for formulas
% INPUTS:	t_value_array:	array containing the t values for which to
%							calculate the cdf
%			df:	degree of freedom; equals n - 1 for the t-distribution

cdf_value_array = 0.5 +...
	((betainc(1, 0.5 * df, 0.5) / beta(0.5 * df, 0.5)) - ...
	(betainc((df ./ (df + t_value_array.^2)), 0.5 * df, 0.5) /...
	beta(0.5 * df, 0.5))) .*...
	sign(t_value_array);

return
end

%-----------------------------------------------------------------------------
function [t_prob_dist] = students_pf(df, t_arr)
%  calculate the probability function for students t-distribution

t_prob_dist =	(df ./ (df + t_arr.^2)).^((1 + df) / 2) /...
	(sqrt(df) * beta(0.5 * df, 0.5));

% % calculate and scale the cdf by hand...
% cdf = cumsum(t_prob_dist);
% discrete_t_cdf = (cdf - min(cdf)) / (max(cdf) - min(cdf));
% % numericaly get the t-value for the given alpha
% tmp_index = find(discrete_t_cdf > (1 - tmp_alpha));
% t_crit = t(tmp_index(1));

return
end

function in = isoctave ()
persistent inout;

if isempty(inout),
	inout = exist('OCTAVE_VERSION','builtin') ~= 0;
end;
in = inout;

return;
end


function [] = display_protocol_stack_information(pre_IP_overhead)
% use [1] http://ace-host.stuart.id.au/russell/files/tc/tc-atm/ to present the
% most likely ATM protocol stack setup for a given overhead so the user can
% compare with his prior knowledge

% how much data fits into ATM cells without padding? 32 cells would be 1519
% which is larger than the 1500 max MTU for ethernet
ATM_31_cells_proto_MTU = 31 * 48;	% according to [1] 31 cells are the optimum for all protocol stacks
ATM_32_cells_proto_MTU = 32 * 48;	% should be best for case 44

disp(' ');
disp('According to http://ace-host.stuart.id.au/russell/files/tc/tc-atm/');
disp(['', num2str(pre_IP_overhead), ' bytes overhead indicate']);

switch pre_IP_overhead
	case 8
		disp('Connection: IPoA, VC/Mux RFC-2684');
		disp('Protocol (bytes): ATM AAL5 SAR (8) : Total 8');
		overhead_bytes_around_MTU = 8;
		overhead_bytes_in_MTU = 0;
		
	case 16
		disp('Connection: IPoA, LLC/SNAP RFC-2684');
		disp('Protocol (bytes): ATM LLC (3), ATM SNAP (5), ATM AAL5 SAR (8) : Total 16');
		overhead_bytes_around_MTU = 16;
		overhead_bytes_in_MTU = 0;
		
	case 24
		disp('Connection: Bridged, VC/Mux RFC-1483/2684');
		disp('Protocol (bytes): Ethernet Header (14), ATM pad (2), ATM AAL5 SAR (8) : Total 24');
		overhead_bytes_around_MTU = 24;
		overhead_bytes_in_MTU = 0;
		
	case 28
		disp('Connection: Bridged, VC/Mux+FCS RFC-1483/2684');
		disp('Protocol (bytes): Ethernet Header (14), Ethernet PAD [8] (0), Ethernet Checksum (4), ATM pad (2), ATM AAL5 SAR (8) : Total 28');
		overhead_bytes_around_MTU = 28;
		overhead_bytes_in_MTU = 0;
		
	case 32
		disp('Connection: Bridged, LLC/SNAP RFC-1483/2684');
		disp('Protocol (bytes): Ethernet Header (14), ATM LLC (3), ATM SNAP (5), ATM pad (2), ATM AAL5 SAR (8) : Total 32');
		overhead_bytes_around_MTU = 32;
		overhead_bytes_in_MTU = 0;
		disp('OR');
		disp('Connection: PPPoE, VC/Mux RFC-2684');
		disp('Protocol (bytes): PPP (2), PPPoE (6), Ethernet Header (14), ATM pad (2), ATM AAL5 SAR (8) : Total 32');
		overhead_bytes_around_MTU = 24;
		overhead_bytes_in_MTU = 8;
		
	case 36
		disp('Connection: Bridged, LLC/SNAP+FCS RFC-1483/2684');
		disp('Protocol (bytes): Ethernet Header (14), Ethernet PAD [8] (0), Ethernet Checksum (4), ATM LLC (3), ATM SNAP (5), ATM pad (2), ATM AAL5 SAR (8) : Total 36');
		overhead_bytes_around_MTU = 36;
		overhead_bytes_in_MTU = 0;
		disp('OR');
		disp('Connection: PPPoE, VC/Mux+FCS RFC-2684');
		disp('Protocol (bytes): PPP (2), PPPoE (6), Ethernet Header (14), Ethernet PAD [8] (0), Ethernet Checksum (4), ATM pad (2), ATM AAL5 SAR (8) : Total 36');
		overhead_bytes_around_MTU = 28;
		overhead_bytes_in_MTU = 8;
		
	case 10
		disp('Connection: PPPoA, VC/Mux RFC-2364');
		disp('Protocol (bytes): PPP (2), ATM AAL5 SAR (8) : Total 10');
		overhead_bytes_around_MTU = 8;
		overhead_bytes_in_MTU = 2;
		
	case 14
		disp('Connection: PPPoA, LLC RFC-2364');
		disp('Protocol (bytes): PPP (2), ATM LLC (3), ATM LLC-NLPID (1), ATM AAL5 SAR (8) : Total 14');
		overhead_bytes_around_MTU = 12;
		overhead_bytes_in_MTU = 2;
		
	case 40
		disp('Connection: PPPoE, LLC/SNAP RFC-2684');
		disp('Protocol (bytes): PPP (2), PPPoE (6), Ethernet Header (14), ATM LLC (3), ATM SNAP (5), ATM pad (2), ATM AAL5 SAR (8) : Total 40');
		overhead_bytes_around_MTU = 32;
		overhead_bytes_in_MTU = 8;
		
	case 44
		disp('Connection: PPPoE, LLC/SNAP+FCS RFC-2684');
		disp('Protocol (bytes): PPP (2), PPPoE (6), Ethernet Header (14), Ethernet PAD [8] (0), Ethernet Checksum (4), ATM LLC (3), ATM SNAP (5), ATM pad (2), ATM AAL5 SAR (8) : Total 44');
		overhead_bytes_around_MTU = 36;
		overhead_bytes_in_MTU = 8;
		
	otherwise
		disp('a protocol stack this program does NOT know (yet)...');
end

disp(' ');
return;
end


function range_mean = robust_mean(value_list, lower_limit_ratio, upper_limit_ratio)

n_vals = length(value_list);
sorted_values = sort(value_list);

lowest_robust_idx = ceil(n_vals * lower_limit_ratio);
highest_robust_idx = floor(n_vals * upper_limit_ratio);

range_mean = mean(sorted_values(lowest_robust_idx:highest_robust_idx));

return
end

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[-- Attachment #4: ping_sweeper5_dp.sh --]
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#! /bin/bash
# TODO use seq or bash to generate a list of the requested sizes (to alow for non-equdistantly spaced sizes)

# just an identifier for the ping log
TECH=ADSL
# finding a proper target IP is somewhat of an art, just traceroute a remote site 
# and find the nearest host reliably responding to pings showing the smallet variation of pingtimes
# for this I typically run "traceroute 8.8.8.8", and then select the first host on the ISP side (typically after 
# the first large RTT increment) and test its response by "ping -c 10 -s 16 NNN.NNN.NNN.NNN", if this host does not repsond 
# I pick the next host along the route to 8.8.8.8. I assume the closer the host the less disturbed by other traffic the 
# response will be.

echo "Edit and set TARGET to a valid IPv4 host-address, end comment the exit"
exit 0

TARGET=${1}		# Replace by an appropriate host



DATESTR=`date +%Y%m%d_%H%M%S`	# to allow multiple sequential records
LOG=ping_sweep_${TECH}_${DATESTR}.txt

MAX_PREIP_OVERHEAD_SIZE=44	# as far as I can tell 44 bytes is the maximum pre IP header overhead for an ATM based carrier
IP4_HEADER_SIZE=20		# 20 bytes
IDEAL_MTU=1500			#  what the MTU should look like

# by default non-root ping will only end one packet per second, so work around that by calling ping independently for each package
# empirically figure out the shortest period still giving the standard ping time (to avoid being slow-pathed by our host)
# at 100 packets/s of 116 + 28 + 40 we would need 4 ATM cells = 192byte * 100/s = 150kbit/s
# at 100 packets/s of 16 + 28 + 40nwe would need 2 ATM cells = 96byte * 100/s = 75kbit/s
# on average we need 150 + 75 * 0.5 = 112.5 Kbit/s, increase the ping period if uplinh < 112.5 Kbit/s
PINGPERIOD=0.01		# in seconds, at 100 packets of 116 + 28 + 40 = 3 ATM cells = 192byte * 100/s = 150kbit/s,
PINGSPERSIZE=10000	# the higher the link rate the more samples we need to reliably detect the increasingly smaller ATM quantisation steps.

# Start, needed to find the per packet overhead dependent on the ATM encapsulation
# to reiably show ATM quantization one would like to see at least two steps, so cover a range > 2 ATM cells (so > 96 bytes)
SWEEPMINSIZE=16		# 64bit systems seem to require 16 bytes of payload to include a timestamp...
SWEEPMAXSIZE=116
    

n_SWEEPS=`expr ${SWEEPMAXSIZE} - ${SWEEPMINSIZE}`


i_sweep=0
i_size=0

while [ ${i_sweep} -lt ${PINGSPERSIZE} ]
do
    (( i_sweep++ ))
    echo "Current iteration: ${i_sweep}"
    # now loop from sweepmin to sweepmax
    i_size=${SWEEPMINSIZE}
    while [ ${i_size} -le ${SWEEPMAXSIZE} ]
    do
	echo "${i_sweep}. repetition of ping size ${i_size}"
	ping -c 1 -s ${i_size} ${TARGET} >> ${LOG} &
	(( i_size++ ))
	# we need a sleep binary that allows non integer times (GNU sleep is fine as is sleep of macosx 10.8.4)
	sleep ${PINGPERIOD}
    done
done

#tail -f ${LOG}

echo "Done... ($0)
"

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> 
> I am seeing my effective bandwidth be higher by about 50/KBs on downloads. On Netflix, my Roku used to try HD upon starting playback then (after 20-30 seconds thinking about it) fail back to SD, but now the HD streams are working flawlessly for hours.
> 
> -- 
> David P.
> 
> 
> 
> On Tue, Jan 7, 2014 at 6:34 AM, Sebastian Moeller <moeller0@gmx.de> wrote:
> Hi David,
> 
> 
> On Jan 7, 2014, at 12:08 , David Personette <dperson@gmail.com> wrote:
> 
> > I'm in the US, but live in a relatively rural area. My only internet options are DSL and satellite. The local provider is Century Link (it used to be Sprint, but they sold their copper phone business off). I have the fastest service that they offer (based on distance from the DSLAM), 4 down / .5 up.
> 
>         And you are not alone, a considerable percentage of the population wherever you look is hanging on such connections. So cerowrt should really help those folk as well as luckier ones.
> 
> >
> > I have had SmokePing monitoring my latency to the first hop outside my network for over a year now (I've been on CeroWRT the whole time). My baseline (no load) latency is 31ms. I used to have AQM throttling back to 80% of my already pathetic bandwidth. I would still regularly see periods lasting minutes to hours when latency would be 80 - 120ms.
> >
> > I only recently grokked what you were talking about with tc_stab since I got back from the holidays with the family, I set things up as you suggested for Fred (nfq_codel, "target 25ms" in advanced egress, ATM, per packet overhead 40,
> 
>         The exact number depends on the encapsulation your ISP uses, 40 is right for a typical PPPoE over LLC/SNAP connection, if that is correct for your link you are fine, otherwise contact me if you want to empirically find out the proper value for your link.
> 
> > and set my SQM bandwidth limits to 95%). Since the 30th my "worst case" latency has been 41ms.
> 
>         the fq_codels really are great if in control of the bottleneck, really good work by bright people!
> 
> > Plus I get to use more of my actual bandwidth.
> 
>         Well, that I am not so sure. By enabling link layer ATM the router will automatically take care of the ATM cell overhead for you (basically reducing the effective rate to ~90% of the link, in other words you get the same effect by shaping to 90%). It will also handle the per packet overhead and the nasty potential padding of the last ATM cell (both have a stronger effect on small packets and are hard to actually account for by static rate reduction; link layer ATM comes again to the rescue by taking these two into account individually for each packet based on the packet size). So effectively 95% with link layer adjustments might mean a lower wire rate than 80% without; the important thing is that with the link layer adjustments the link capacity is estimated correctly avoiding the modem's and the DSLAM's buffers to fill and cause buffer bloat.
> 
> > I REALLY wish that I'd made the time to read your emails about setting up the ATM overhead earlier.
> 
>         Oh, I can understand, when I learned about this some years ago (by stumbling over Russel Stuart's website and Jesper Brouer's thesis) it immediate changed my internet experience (I was on a 3 down / 0.5 up connection at that time). :)
> 
> Best Regards
>         Sebastian
> 
> >
> > Thank you.
> >
> > --
> > David P.
> >
> >
> >
> > On Mon, Jan 6, 2014 at 9:27 AM, Sebastian Moeller <moeller0@gmx.de> wrote:
> > Hi Fred,
> >
> >
> > On Jan 6, 2014, at 15:22 , Fred Stratton <fredstratton@imap.cc> wrote:
> >
> > > The line rate is 11744/1022 kb/s, but changes moment to moment. SNR is 12.1 decibel.  I am using 11000/950 kb/s as settings.
> >
> >         So 100 * 11000 / 11744 = 93.66% of downlink line rate and 100* 950 / 1022 = 92.95 % of uplink line rate; quite impressive given the common wisdom of 85% :).
> >
> >
> > >  I shall try your suggestion when there is something worth watching live, to provide a valid comparison, which may not be before 21:30 CET on Sunday.
> >
> >         Oh, take your time, this is really not essential, butit would be a nice data point for figuring out how important the correct overhead estimate really is in real life, theory being theory and all…
> >
> > Best Regards
> >         Sebastian
> >
> > >
> > > On 06/01/14 14:12, Sebastian Moeller wrote:
> > >> Hi Fred,
> > >>
> > >>
> > >> On Jan 6, 2014, at 10:52 , Fred Stratton <fredstratton@imap.cc> wrote:
> > >>
> > >>> I have been operating the latest build with 6relayd disabled. The henet /48 I have been allocated is subnetted correctly, presumably by dnsmasq.
> > >>>
> > >>> I adopted the suggestions to use nfq_codel and an egress target of 25ms , with an overhead of 40 on a PPPoE connection.  I chose to watch the first 2 episodes of the 3 part third series of 'Sherlock', live on iPlayer, and these streamed correctly and uninterrupted for 90 minutes.  This was not previously possible.  (Quite whether they were up to the standard of previous episodes is another matter.)
> > >>>
> > >>> I can watch iPlayer with little stutter whilst downloading Arch Linux by torrent, downloading other files at the same time.
> > >>>
> > >>> So, for a relatively slow ADSL2+ line, the current build works well.
> > >>      Out of curiosity, to what percentage of the "current line rate" (you know the one reported by your modem) you shaped up- and downlink? And in case you have too much time on your hand, how does the same feel with an overhead of 10 (to see how bad an overhead underestimate would feel for a user), since you currently happen to have a quite sensitive subjective latency evaluation system set up :)…
> > >>
> > >> Best Regards
> > >>      Sebastian
> > >>
> > >>>
> > >>> On 06/01/14 03:29, Dave Taht wrote:
> > >>>> On Sat, Jan 4, 2014 at 10:40 AM, Fred Stratton <fredstratton@imap.cc> wrote:
> > >>>>> Link Names:
> > >>>>>
> > >>>>> For consistency, if ADSL is used as a portmanteau term, them VDSL should be
> > >>>>> used as the equivalent for VDSL and VDSL2.
> > >>>>>
> > >>>>> CeroWRT has to decide whether it is an experimental build, or something that
> > >>>>> will eventually be used in production, so these decisions can be made
> > >>>>> consistently.
> > >>>> Well, what I was aiming for was for us to get the sqm scripts and gui
> > >>>> up to where they were better than the standard openwrt qos scripts and
> > >>>> then push them up to openwrt to where they could be more widely
> > >>>> deployed.
> > >>>>
> > >>>> Aside from being able to dynamically assign priorities in the gui, we
> > >>>> are there.  Except that nfq_codel is currently getting better results
> > >>>> than fq_codel at low bandwidths, and I'm tempted to pour all of
> > >>>> simple.qos into C.
> > >>>>
> > >>>> As for cero's future - certainly since all the snowden revelations
> > >>>> I've been going around saying that "friends don't let friends run
> > >>>> factory firmware". I would like a stable build of sqm and cerowrt to
> > >>>> emerge, and to then go off and work on improving wifi. Regrettably
> > >>>> what seems to be happening is more backwards than forwards on the
> > >>>> former, and ramping up on the ath9k and ath10k is taking more time
> > >>>> than I'd like, and it seems likely I'll be working on those primarily
> > >>>> on another platform and only eventually pushing the results out to
> > >>>> cero, mainline kernel
> > >>>>
> > >>>> So it's still at the "keep plugging away" point for sqm, ipv6, cero in
> > >>>> general, with the stable release always just out of sight.
> > >>>>
> > >>>> Tackling the ipv6 problem is next on my agenda on cero, and getting a
> > >>>> test suite going is next on my day job.
> > >>>>
> > >>>>> I concur with your ADSL setup suggestion as default. I have been running the
> > >>>>> Sebastian Moeller ping script overnight to calculate ADSL overhead for the
> > >>>>> last several days. After several hours of curve fitting using Octave, an
> > >>>>> overhead result is displayed. This novel approach works well.
> > >>>> It would be nice to get to where we could autoconfigure a router using
> > >>>> tools like these with no human intervention. This includes bandwidth
> > >>>> estimation.
> > >>>>
> > >>>>> The overhead for the particular setup I use was 40 for PPPoE, and 10 for
> > >>>>> PPPoA.
> > >>>>>
> > >>>>> The default you suggest is a suitable starting point, I suggest.
> > >>>>>
> > >>>>>
> > >>>>> On 04/01/14 18:16, Rich Brown wrote:
> > >>>>>> QUESTION #5: I still don’t have any great answers for the Link Layer
> > >>>>>> Adaptation overhead descriptions and recommendations. In an earlier message,
> > >>>>>> (see
> > >>>>>> https://lists.bufferbloat.net/pipermail/cerowrt-devel/2013-December/001914.html
> > >>>>>> and following messages), Fred Stratton described the overheads carried by
> > >>>>>> various options, and Sebastian Moeller also gave some useful advice.
> > >>>>>>
> > >>>>>> After looking at the options, I despair of giving people a clear
> > >>>>>> recommendation that would be optimal for their equipment. Consequently, I
> > >>>>>> believe the best we can do is come up with “good enough” recommendations
> > >>>>>> that are not wrong, and still give decent performance.
> > >>>>>>
> > >>>>>> In this spirit, I have changed Draft #3 of the “Setting up SQM” page to
> > >>>>>> reflect this understanding. See
> > >>>>>> http://www.bufferbloat.net/projects/cerowrt/wiki/Setting_up_AQM_for_CeroWrt_310
> > >>>>>>
> > >>>>>>         ADSL/ATM link: Choose “ADSL/ATM", and set Per Packet Overhead to
> > >>>>>> 40
> > >>>>>>         VDSL2 link: Choose “VDSL”, and set Per Packet Overhead to 8
> > >>>>>>         Other kind of link (e.g., Cable, Fiber, Ethernet, other not
> > >>>>>> listed): Choose “None (default)”, and set Per Packet Overhead to 0
> > >>>>>>
> > >>>>>> NB: I have changed the first menu choice to “ADSL/ATM” and the second to
> > >>>>>> “VDSL” in the description. I would ask that we change to GUI to reflect
> > >>>>>> those names as well. This makes it far easier/less confusing to talk about
> > >>>>>> the options.
> > >>>>>>
> > >>>>>> As always, I welcome help in setting out clear recommendations that work
> > >>>>>> well for the vast majority of people who try CeroWrt. Thanks.
> > >>>>>>
> > >>>>>> Rich
> > >>>>>> _______________________________________________
> > >>>>>> Cerowrt-devel mailing list
> > >>>>>> Cerowrt-devel@lists.bufferbloat.net
> > >>>>>> https://lists.bufferbloat.net/listinfo/cerowrt-devel
> > >>>>> _______________________________________________
> > >>>>> Cerowrt-devel mailing list
> > >>>>> Cerowrt-devel@lists.bufferbloat.net
> > >>>>> https://lists.bufferbloat.net/listinfo/cerowrt-devel
> > >>>>
> > >>> _______________________________________________
> > >>> Cerowrt-devel mailing list
> > >>> Cerowrt-devel@lists.bufferbloat.net
> > >>> https://lists.bufferbloat.net/listinfo/cerowrt-devel
> > >
> >
> > _______________________________________________
> > Cerowrt-devel mailing list
> > Cerowrt-devel@lists.bufferbloat.net
> > https://lists.bufferbloat.net/listinfo/cerowrt-devel
> >
> 
>