def impactOfEta(outdir):
N = 8
D = 4096
a = 10
l = 0
r = 10
e = 0
X = [4, 8, 16, 32, 64, 128]
tpcY = []
tideY = []
tpc5Y = []
for d in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, 100, 0)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, 1, 0.5)
tpc5Y.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
ltpc5 = axes.plot(X, tpc5Y, '-*g')
axes.set_xlabel('Number of Data Item')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide, ltpc5), ('tpc', 'tide', 'tpc5'))
fig.savefig('%s/impact_of_eta.pdf' % outdir)
def impactOfEta(outdir):
N = 8
D = 4096
a = 10
l = 0
r = 10
e = 0
X = [4, 8, 16, 32, 64, 128]
tpcY = []
tideY = []
tpc5Y = []
for d in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, 100, 0)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, 1, 0.5)
tpc5Y.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
ltpc5 = axes.plot(X, tpc5Y, '-*g')
axes.set_xlabel('Number of Data Item')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide, ltpc5), ('tpc', 'tide', 'tpc5'))
fig.savefig('%s/impact_of_eta.pdf'%outdir)
def impactOfMaxNumTxns(outdir):
D = 4096
d = 32
a = 100
l = 80
r = 10
b = 100
eta = 0
e = 20
X = [2, 4, 8, 16, 32, 64]
tpcY = []
tideY = []
for N in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, b, eta)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
axes.set_xlabel('Max Number of Txns')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide), ('tpc', 'tide'))
fig.savefig('%s/impact_of_max_num_txns.pdf' % outdir)
def impactOfExecTime(outdir):
N = 64
D = 4096
d = 32
a = 100
l = 10
b = 100
eta = 0
e = 20
X = [10, 20, 30, 40, 50]
tpcY = []
tideY = []
for r in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, b, eta)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
axes.set_xlabel('Average Txn Execution Time')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide), ('tpc', 'tide'))
fig.savefig('%s/impact_of_exec_time.pdf' % outdir)
def impactOfLambda(outdir):
N = 64
D = 4096
d = 32
l = 80
r = 10
b = 100
eta = 0
e = 20
X = [20, 40, 60, 80, 100]
tpcY = []
tideY = []
for a in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, b, eta)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
axes.set_xlabel('Average Txn Arrive Interval')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide), ('tpc', 'tide'))
fig.savefig('%s/impact_of_lambda.pdf' % outdir)
def impactOfMaxNumTxns(outdir):
D = 4096
d = 32
a = 100
l = 80
r = 10
b = 100
eta = 0
e = 20
X = [2, 4, 8, 16, 32, 64]
tpcY = []
tideY = []
for N in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, b, eta)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
axes.set_xlabel('Max Number of Txns')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide), ('tpc', 'tide'))
fig.savefig('%s/impact_of_max_num_txns.pdf'%outdir)
def impactOfExecTime(outdir):
N = 64
D = 4096
d = 32
a = 100
l = 10
b = 100
eta = 0
e = 20
X = [10, 20, 30, 40, 50]
tpcY = []
tideY = []
for r in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, b, eta)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
axes.set_xlabel('Average Txn Execution Time')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide), ('tpc', 'tide'))
fig.savefig('%s/impact_of_exec_time.pdf'%outdir)
def impactOfLambda(outdir):
N = 64
D = 4096
d = 32
l = 80
r = 10
b = 100
eta = 0
e = 20
X = [20, 40, 60, 80, 100]
tpcY = []
tideY = []
for a in X:
nw, nr, nq, loss, ts = runTPCModel(N, D, d, a, l, r, b, eta)
tpcY.append(ts)
nw, nr, nq, loss, ts = runTideModel(N, D, d, a, l, r, e)
tideY.append(ts)
fig = plt.figure()
axes = fig.add_subplot(111)
ltpc = axes.plot(X, tpcY, '-ob')
ltide = axes.plot(X, tideY, '-+r')
axes.set_xlabel('Average Txn Arrive Interval')
axes.set_ylabel('Average Txn Service Time')
fig.legend((ltpc, ltide), ('tpc', 'tide'))
fig.savefig('%s/impact_of_lambda.pdf'%outdir)