平衡边界作业算法并发仿真测试基于三层架构的Web系统的基准性能

clear;

% input
N1 = input('Number of customers of class 1 N1 = ');   % number of customers of class 1
N2 = input('Number of customers of class 2 N2 = ');   %  number of customers of class 2
M = input('number of applicaion tiers M = ');         % number of applicaion tiers

for k = 2:(M+1)
S1(k) = input('Average service time S1 = ');  % average service time per tier of class 1
V1(k) = input('Visit number V1 = ');          % visit number per tier of class 1
end
Z1 = input('Think time Z1 = ');         % average think time of class 1

for k = 2:(M+1)
S2(k) = input('Average service time S2 = ');  % average service time per tier of class 2
V2(k) = input('Visit number V2 = ');          % visit number per tier of class 2
end
Z2 = input('Think time Z2 = ');         % average think time of class 2

% initialization
S1(1) = Z1;
V1(1) = 1;
for m = 1:(M+1)
D1(m) = V1(m) * S1(m);              % service demand per tier of class 1
end

S2(1) = Z2;
V2(1) = 1;
for m = 1:(M+1)
D2(m) = V2(m) * S2(m);              % service demand per tier of class 2
end

vN2 = [1 5:5:N2];

for n = 1:length(vN2)                   % up to a maximum number of customers
N2 = vN2(n);

% APPROXIMATE MVA ALGORITHM
% initialization
for m = 2:(M+1)
Q1(m) = N1/M;
Q2(m) = N2/M;
end
error = [1 1 1 1 1 1];

R1(1) = D1(1);
R2(1) = D2(1);

while max(error) > 0.01
for m = 2:(M+1)
A1(m) = (N1-1)/N1*Q1(m) + Q2(m);        % average number of customers per tier of class 1
A2(m) = (N2-1)/N2*Q2(m) + Q1(m);        % average number of customers per tier of class 2
end

for m = 2:(M+1)
R1(m) = D1(m) * (1 + A1(m));            % average delay per tier of class 1
R2(m) = D2(m) * (1 + A2(m));            % average delay per tier of class 2
end

X1 = N1 / (sum(R1(:)));         % throughput of class 1
X2 = N2 / (sum(R2(:)));         % throughput of class 2

for m = 2:(M+1)
Q1old(m) = Q1(m);           % old length of queue 1
Q2old(m) = Q2(m);           % old length of queue 2
Q1(m) = X1 * R1(m);         % new length of queue 1
Q2(m) = X2 * R2(m);         % new length of queue 2
end

for m = 2:(M+1)
error(m-1) = abs((Q1(m) - Q1old(m)) / Q1old(m));
error(m-1+M) = abs((Q2(m) - Q2old(m)) / Q2old(m));
end
end

for m = 2:(M+1)
U1n(n,m) = X1 * S1(m) * V1(m);  % tier utilization of class 1
U2n(n,m) = X2 * S2(m) * V2(m);  % tier utilization of class 2
end

X1n(n) = X1;                        % throughput of class 1
X2n(n) = X2;                        % throughput of class 2

RT1n(n) = sum(R1(2:(M+1)));         % response time of class 1
RT2n(n) = sum(R2(2:(M+1)));         % response time of class 2
end

% BALANCED JOB BOUNDS
D1max = max(D1(2:(M+1)));               % maximum service demand per queue of class 1
D2max = max(D2(2:(M+1)));               % maximum service demand per queue of class 2
D1sum = sum(D1(2:(M+1)));               % sum of total service demands of class 1
D2sum = sum(D2(2:(M+1)));               % sum of total service demands of class 2
D1avg = D1sum/M;                        % average service demand per queue of class 1
D2avg = D2sum/M;                        % average service demand per queue of class 2
for n = 1:length(vN2)
N = vN2(n) + N1;
R2min(n) = max(N * D2max - Z2, D2sum + ((N-1)*D2avg*D2sum/(D2sum+Z2))); % lower bound of response time
R2max(n) = D2sum + ((N-1)*D2max*(N-1)*D2sum/(((N-1)*D2sum)+Z2));        % upper bound of response time

X2min(n) = vN2(n) / (Z2 + R2max(n));            % lower bound of throughput
X2max(n) = vN2(n) / (Z2 + R2min(n));            % upper bound of throughput

for m = 2:(M+1)
U2minm(n,m) = X2min(n) * D2(m);            % lower bound of utilization per tier
U2maxm(n,m) = X2max(n) * D2(m);            % upper bound of utilization per tier
end
end

t = vN2;

% response time
figure(1), plot(t, RT2n,'r', t, R2min, 'g', t, R2max, 'b'), xlabel('Simultaneous browser connections'), ylabel('Response time(s)');

% throughput
figure(2), plot(t, X2n,'r', t,X2min,'g', t, X2max, 'b'), xlabel('Simultaneous browser connections'), ylabel('Throughput(1/s)');