sim_obstaclep.m

best routing protocol

function sim_obstaclep(instance, job_id)
% job_id: 
%  >0  -- called in condor for specific jobs, never use it manually
%  except for debugging!
%  ==0 -- called by user: run all jobs without using condor
% unspecified -- save consts and schedule condor jobs
% ==-1 -- don't calculate. only process and plot!

%run size experiment in parallel
%this is different from sim_size in that each simulation uses a new
%topology file

fn = 'sim_obstaclep';
MAX_JOBS = 100;
if nargin==2
  if job_id == -1
    process_data(fn, instance)
  else
    get_raw_data(fn, instance, [job_id], MAX_JOBS)
  end
  return
end
total_jobs = get_raw_data(fn, instance, [], MAX_JOBS)
fid = fopen('condor.matlab','wt');
if fid<0
  error('could not open file');
end

fprintf(fid, '%s %s %d\n', fn, instance, min(total_jobs,MAX_JOBS));
fclose(fid);
! python gen_condor_jobs.py

function job_count = get_raw_data(fn, instance, job_ids, max_jobs)

n_obstacles = [0 25, 50, 75];
l_obstacles = [1.25, 2.5];
repeat = 10;
const_fn = sprintf('%s/%s-const.mat', instance, fn);

if length(job_ids)==0 | ismember(0, job_ids)
  const_fn = sprintf('%s/%s-const.mat', instance, fn);
  save(const_fn, 'repeat', 'n_obstacles','l_obstacles','max_jobs','-V6');
end

load(const_fn); %make sure it's consistant between instances

job_count = 0;

%%%%%%%
for i=1:repeat
  for n=1:length(n_obstacles)
    for l=1:length(l_obstacles)
      job_count = job_count + 1;
      if schedule_job(job_count, job_ids, max_jobs)
	final_fn = sprintf('%s/%s-%d.mat', instance, fn, job_count);
	fprintf('**job_id=%d*  i=%d\n', job_count, i);
	try
	  tmp=load(final_fn);
	  clear tmp
	  fprintf('**ALREADY DID job_id=%d**\n', job_count);
	catch
	  topo=sprintf('%s/topo-obstacle-%d-%1.2f-%d.mat',instance,n_obstacles(n),l_obstacles(l),i)
	  topology_generator(topo,3200, 5.12, n_obstacles(n), l_obstacles(l),0);
	  fprintf('****sim_obstacle test %s, repeat=%d\n', topo, i);
	  res = simulation(topo, 56);
	  optimal = sim_optimal(topo);
	  save(final_fn ,'res','optimal');
	end
      end
    end
  end
end

function process_data(fn, instance)

load(sprintf('%s/%s-const.mat', instance,fn))
job_count = 0;
for i=1:repeat
  for n=1:length(n_obstacles)
    for l=1:length(l_obstacles)
      job_count = job_count + 1;
      final_fn = sprintf('%s/%s-%d.mat', instance, fn, job_count);
      TMP = load(final_fn);
      res(n,l,i) = TMP.res;
      optimal(n,l,i) = TMP.optimal;
      topo_fn = sprintf('%s/topo-obstacle-%d-%1.2f-%d.mat',instance, ...
		   n_obstacles(n),l_obstacles(l),i);
      S = load(topo_fn);
      total_links = sum(S.D(:));
      n_blocked(n,l,i) = S.n_blocked/(S.n_blocked+total_links);
    end
  end
end
save(sprintf('%s/%s-all.mat',instance,fn));

plot_data(sprintf('%s/%s-all.mat',instance,fn))
function plot_data(fn)
%copied from sim_obstacle.m's process_data
%not really plot, but output into the table file
load(fn);
fid = fopen('obstacle.table','w');

for l=1:length(l_obstacles)
  for n=1:length(n_obstacles)
    clear stretch_bvr_sf_mean
    for i=1:repeat
      stretch_bvr_sf_mean(i)=plot_routing_stretch( ...
	  res(n,l,i).transmission_dist_bvr_sf', optimal(n,l,i).optimal_dist, 'k',[50],0);

      stretch_bvr_sf_worst(i)=plot_routing_stretch( ...
	  res(n,l,i).transmission_dist_bvr_sf', optimal(n,l,i).optimal_dist, 'k',[95],0);
      
      stretch_bvr_2h_mean(i)=plot_routing_stretch( ...
	  res(n,l,i).transmission_dist_bvr_2h', optimal(n,l,i).optimal_dist, 'k',[50],0);

      stretch_cr_mean(i)=plot_routing_stretch( ...
	  res(n,l,i).routing_dist_cr, optimal(n,l,i).optimal_dist, 'k',[50],0);

      stretch_cr_worst(i)=plot_routing_stretch( ...
	  res(n,l,i).routing_dist_cr, optimal(n,l,i).optimal_dist, 'k',[95],0);
      
      failure_bvr(i) = res(n,l,i).failure_bvr;
      
    end
    fprintf('number:%d,length:%1.2f avg stretch bvr %f(%f)\t cr %f(%f) n_blocked:%f\n', ...
	    n_obstacles(n), l_obstacles(l), ...
	    mean(stretch_bvr_sf_mean), ...
	    mean(stretch_bvr_sf_worst),...
	    mean(stretch_cr_mean), ...
	    mean(stretch_cr_worst),...
	    mean(n_blocked(n,l,:)));
    %cr_final(l,n)=mean(stretch_cr_mean);
    %bvr_final(l,n) = mean(stretch_bvr_sf_mean);
    cr_final(l,n)=mean(stretch_cr_worst);
    bvr_final(l,n) = mean(stretch_bvr_sf_worst);
  end
end

% for the case without obstacle, return the averaged result
bvr_final(1,1) = (bvr_final(1,1)+bvr_final(2,1))/2;
bvr_final(2,1) = bvr_final(1,1);

cr_final(1,1) = (cr_final(1,1)+cr_final(2,1))/2;
cr_final(2,1) = cr_final(1,1);

for l=1:length(l_obstacles)
  fprintf(fid, '%.2f & ', l_obstacles(l));
  for n=1:length(n_obstacles)
    fprintf(fid, '%.2f, %.2f ', cr_final(l,n),bvr_final(l,n));
    if n<length(n_obstacles)
      fprintf(fid,' & ');
    else
      fprintf(fid,'\\\\\n');
    end
  end
end

fclose(fid);

%%%%%%%%%%%%%%%%%
fontsize=20;
msz = 12;
lwd = 2;
set(gca, 'FontSize', fontsize);

hold on
plot(n_obstacles, cr_final(1,:),'go-','MarkerSize', msz, 'LineWidth',lwd);
plot(n_obstacles, cr_final(2,:),'r<-','MarkerSize', msz, 'LineWidth',lwd)
plot(n_obstacles, bvr_final(1,:),'k*-','MarkerSize', msz, 'LineWidth',lwd)
plot(n_obstacles, bvr_final(2,:),'k^-','MarkerSize', msz, 'LineWidth',lwd)
xlabel('number of obstacles');
ylabel('95th percentile transmission stretch');
legend('S4, obstacle len=1.25','S4, obstacle len=2.5',...
  'BVR, obstacle len=1.25','BVR, obstacle len=2.5','Location','Best');
saveas(gcf, 'obstacle.eps','psc2')