Research Article

Multiobjective Level-Wise Scientific Workflow Optimization in IaaS Public Cloud Environment

Table 4

Convergence, diversity, and execution time for SPEA2 and NSGA−II.

Workflow AlgorithmAvg. Conv. (±σ)Avg. Div. (±σ)Avg. Exec. (sec) (±σ)

Epigenomics_24SPEA20.0240 (±0.0011)1.8554 (±0.0367)406.5189 (±14.9)
NSGA-II0.0294 (±0.0177)1.7936 (±0.0992)74.5451 (±6.5)
Montage_25SPEA20.0060 (±0.0039)1.0104 (±0.4130)372.7346 (±26.9)
NSGA-II0.0059 (±0.0005)1.2770 (±0.1713)68.5270 (±16.2)
CyberShake_30SPEA20.0094 (±0.0012)1.3485 (±0.0019)414.6732 (±11.0)
NSGA-II0.0079 (±0.0012)1.4026 (±0.0642)53.9493 (±1.8)
Epigenomics_46SPEA20.1661 (±0.2064)1.7670 (±0.0390)431.8035 (±30.5)
NSGA-II0.1118 (±0.0857)1.7152 (±0.0918)71.5525 (±5.5)
Montage_50SPEA20.0033 (±0.0040)1.4672 (±0.1394)366.6482 (±21.9)
NSGA-II0.0100 (±0.0031)1.2758 (±0.1414)63.8932 (±4.6)
CyberShake_50SPEA20.0209 (±0.0077)1.3629 (±0.1168)415.7871 (±17.6)
NSGA-II0.0224 (±0.0060)1.3372 (±0.9048)56.6219 (±3.5)
Epigenomics_100SPEA20.1005 (±0.0518)1.7229 (±0.0079)388.3032 (±13.0)
NSGA-II0.1423 (±0.1108)1.7188 (±0.0004)74.4787 (±6.3)
Montage_100SPEA20.0178 (±0.0140)1.1626 (±0.2073)375.2320 (±13.3)
NSGA-II0.0178 (±0.0055)1.2122 (±0.1533)71.6682 (±10.1)
CyberShake_100SPEA20.0731 (±0.0116)1.0607 (±0.0361)388.4410 (±10.4)
NSGA-II0.0721 (±0.0240)1.2178 (±0.0665)60.2484 (±5.0)
Epigenomics_997SPEA22.3735 (±1.7707)1.5694 (±0.0521)545.0587 (±16.3)
NSGA-II12.652 (±6.5924)1.5404 (±0.0777)225.4969 (±15.7)
Montage_1000SPEA20.0027 (±0.0044)1.5974 (±0.1057)546.3927 (±27.2)
NSGA-II0.0573 (±0.0188)1.6398 (±0.1235)216.1495 (±4.0)
CyberShake_1000SPEA20.2783 (±0.0532)1.1775 (±0.1606)522.4185 (±18.7)
NSGA-II0.3458 (±0.1087)1.3284 (±0.0589)170.0315 (±3.7)