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250
0.02
rr1
random
ENR
ECJ(R=inf)
ECJ(R=0)
ε
acc
rr1
random
ENR
ECJ(R=inf)
ECJ(R=0)
240
0.015
230
220
0.01
210
200
0.005
190
0
180
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
0
0.05 0.1 0.15 0.2 0.25 0.3 0.35
f
f
(a) Error-rate
(b) Computation time
T
Figure 29. Error rate and Computation time for fraction
f
(
acc
=0.01
,
s =0.1
,
c =0.0
,
q =0.2
,
p
d
=0
, without blacklisting).
0.02
245
r
r
1
random
ENR
ECJ(R=inf)
EC
J
(R=
0
)
rr1
random
ENR
ECJ(R=inf)
ECJ(R=0)
ε
acc
0.018
240
0.016
235
0.014
230
0.012
225
0.01
220
0.008
215
0.006
210
0.004
205
0.002
200
0
0
0.2
0.4
0.6
0.8
1
0
0.2
0.4
0.6
0.8
1
c
c
(b) Computation time
T
(a) Error-rate
Figure 30. Error rate and Computation time for colluding rate
c
(
acc
=0.01
,
s =0.1
,
f =0.35
,
c =0.0
,
q =0.2
,
p
d
=0
, without blacklisting).
jobs having incorrect results are selected repeatedly and the number of unnecessary job al-
locations increases. For that reason,
EC
J
(R = inf)
method requires a longer computation
time, as shown in Fig.27 (b).
By selecting jobs in the ascending order of
ENR
, a job having numerous results is not
selected in job scheduling even if the job has incorrect results. In this case, the unnecessary
job allocations do not become numerous, as with the
EC
J
(R =0)
. Therefore, the varia-
tions of the proposed method
EC
J
(R =0)
, which selects jobs in the ascending order of
ENR
at first (
R =0
) and then selects a job based on
EC
J
, shows better performance.
Fig.28 (b) shows computation time
T
as a function of sabotage rate
s
for
q =0.2
.
When the value of
q
becomes larger, all saboteurs are frequently detected by more spot-
checking and no incorrect result remains in the system. In this case, the computation time
