stat_plot_delay

0001 function [cdf_delay_mcn,prctile_mcn]=stat_plot_delay(model,nb_mob,threshold,export,format)
0002 
0003 res.models = { 'street' 'city' 'hexagonal' };
0004 res.model = char(res.models(model));
0005 
0006 res.mob    = nb_mob;
0007 
0008 res.tmax = 60;
0009 
0010 temp_cdf_delay_mcn = [];
0011 temp_cdf_delay_std = [];
0012 
0013 for cov = 1:20
0014     res.coverages = 5:5:100;
0015     res.coverage = res.coverages(cov);
0016 
0017     cdfmcn2load = sprintf('%s/%dusr/%02dcov/cdf-delay-mcn.dat',res.model,res.mob,res.coverage);
0018     load(cdfmcn2load);
0019     cdfstd2load = sprintf('%s/%dusr/%02dcov/cdf-delay-std.dat',res.model,res.mob,res.coverage);
0020     load(cdfstd2load);
0021 
0022     temp_cdf_delay_mcn = [temp_cdf_delay_mcn cdf_delay_mcn];
0023     prctile_mcn(cov) = cdf2prctile(cdf_delay_mcn,threshold);
0024 
0025     temp_cdf_delay_std = [temp_cdf_delay_std cdf_delay_std];
0026     prctile_std(cov) = cdf2prctile(cdf_delay_std,threshold);
0027 
0028     delivmcn2load = sprintf('%s/%dusr/%02dcov/mcn-delivered.dat',res.model,res.mob,res.coverage);
0029     load(delivmcn2load);
0030     delivstd2load = sprintf('%s/%dusr/%02dcov/std-delivered.dat',res.model,res.mob,res.coverage);
0031     load(delivstd2load);
0032 
0033     temp_mcn_delivered(cov) = mcn_delivered;
0034     temp_std_delivered(cov) = std_delivered;
0035 
0036     clear cdf_delay_mcn cdf_delay_std mcn_delivered std_delivered;
0037 end
0038 
0039 cdf_delay_mcn = temp_cdf_delay_mcn;
0040 cdf_delay_std = temp_cdf_delay_std;
0041 
0042 mcn_delivered = temp_mcn_delivered;
0043 std_delivered = temp_std_delivered;
0044 
0045 save('cdf-delay-mcn.dat','cdf_delay_mcn','-ascii','-tabs');
0046 save('cdf-delay-std.dat','cdf_delay_std','-ascii','-tabs');
0047 save(['prctile-' num2str(threshold*100) '%-mcn.dat'],'prctile_mcn','-ascii','-tabs');
0048 save(['prctile-' num2str(threshold*100) '%-std.dat'],'prctile_std','-ascii','-tabs');
0049 %save('prctile-std.dat','prctile_std','-ascii','-tabs');
0050 
0051 %unix(['mkdir ',sprintf('%s/%dusr/%02dcov',res.model,res.mob,res.coverage)]);
0052 unix(['mv *.dat ',sprintf('%s/%dusr/',res.model,res.mob)]);
0053 
0054 
0055 % plot the cdf for the relative delay
0056 stat_plot_delay_cdf(1,cdf_delay_mcn',res.model,res.mob,res.tmax,'multihop',export,format)
0057 
0058 % plot the percentile for the relative delay
0059 stat_plot_delay_prctile(2,prctile_mcn',res.model,res.mob,res.tmax,'multihop',threshold,'b',export,format)
0060 
0061 % plot the cdf for the relative delay
0062 stat_plot_delay_cdf(3,cdf_delay_std',res.model,res.mob,res.tmax,'no multihop',export,format)
0063 
0064 % plot the percentile for the relative delay
0065 stat_plot_delay_prctile(4,prctile_std',res.model,res.mob,res.tmax,'no multihop',threshold,'r',export,format)
0066 
0067 figure(5)
0068 plot([5:5:100],mcn_delivered','b',[5:5:100],std_delivered','r')
0069 grid  ('on')
0070 axis([0 100 0 1])
0071 xlabel('coverage in %')
0072 ylabel('nb msg delivered / nb msg generated')
0073 legend('"store-and-forward"','"store only"',4)
0074 title(sprintf('percentage of messages sucessfully delivered (%s model, %d users, %d min)',res.model,res.mob,res.tmax))
0075 if export == 1
0076     exportfig(gcf,[res.model '-' num2str(res.mob) 'usr-delivered' ],'color', 'cmyk','format',format);
0077 end
0078