availability.m

To Calculate QOS and how it affects Security

MTBF1= input('Enter the First Mean time Between Failure in hours ');
MTBF2= input('Enter the Second Mean time Between Failure in hours ');
MTBF3= input('Enter the Third Mean time Between Failure in hours ');
MTBF4= input('Enter the Fourth Mean time Between Failure in hours ');
MTTRs = input('Enter the Mean time To Repair in hours For Calculating Serviceability ') ;
MTTR = linspace(0,1000,100);
%Availability
%%% Availability = (MTBF/(MTBF+MTTR)) * 100%
%% MTBF is mean time between failure
%% MTTR is mean time to repair 
%% MTBF is the Inverse of ? 
%% ? is the Failure Rate
%% MTBF = 1/?
%% MTTR is directly Proportional to Message Latency 
%% MTTR ~ 8d
%% d is the message latency in time
%% Failure Rate 
%% ? is calculated as the Percentage of failed nodes within WSN 
for i=1:100
    a1(i)=MTTR(i)+MTBF1;
end
for i=1:100
    av1(i)=MTBF1/a1(i);
end
for i=1:100
    a2(i)=MTTR(i)+MTBF2;
end
for i=1:100
    av2(i)=MTBF2/a2(i);
end
for i=1:100
    a3(i)=MTTR(i)+MTBF3;
end
for i=1:100
    av3(i)=MTBF3/a3(i);
end
for i=1:100
    a4(i)=MTTR(i)+MTBF4;
end
for i=1:100
    av4(i)=MTBF4/a4(i);
end
av = [ av1 av2 av3 av4];
MTTR= [ MTTR MTTR MTTR MTTR];
subplot(2,2,1);
plot(MTTR,av);

%% Reliability
%%R(t) = exp(-?t)
%% ? is Failure Rate (Inverse of MTBF)
%% t is the length of time the system must function 
%% R(t) is reliability over time t

t = linspace(0,10000,1000);
for i=1:1000
        rel(i)= exp(-(t(i)/MTBF1));
end
subplot(2,2,2);
plot(t,rel);

%%Serviceability
t1 = linspace(0,100,1000);

for i=1:1000
        ser(i)= exp(-(t1(i)/MTTRs));
end
subplot(2,2,3)
plot(t1,ser);