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Table 3 The comparison of results among the algorithms in each tested VMP problem

From: Improved multiobjective salp swarm optimization for virtual machine placement in cloud computing

  MOSSASCA MOSCA MOPSO MOEAD NSGAII
Power consumption
 VM50-PM25
  Min 4.22 4.24 4.77 4.77 4.41
  Max 6.25 8.25 6.78 6.78 7.68
  Std 0.55 0.97 0.62 0.66 0.73
VM150-PM75
  Min 11.06 11.98 14.25 13.27 12.20
  Max 17.73 14.25 23.85 24.58 19.91
  STD 1.75 0.66 1.96 2.93 2.46
 VM200-PM100
  Min 13.03 14.24 14.78 15.77 13.37
  Max 18.92 19.77 22.04 19.77 19.49
  STD 1.73 1.99 2.26 1.35 1.82
SLAV
 VM50-PM25
  Min 10.00 10.00 10.00 10.00 10.30
  Max 14.94 16.10 18.50 17.00 14.90
  STD 1.63 1.75 2.58 2.24 1.50
 VM150-PM75
  Min 9.67 9.67 9.67 9.67 10.21
  Max 13.29 14.16 14.07 14.07 13.62
  STD 1.60 0.97 1.76 1.98 1.25
 VM200-PM100
  Min 9.60 10.00 10.00 10.00 10.00
  Max 12.13 13.33 14.00 14.00 15.00
  STD 1.15 1.00 1.72 1.45 1.96
MTBHS
 VM50-PM25
  Min 8845.46 7397.86 8538.01 8547.97 7942.10
  Max 10860.11 10773.76 8739.08 8724.04 8566.20
  STD 868.70 856.34 45.33 64.88 192.77
 VM150-PM75
  Min 7630.12 7613.31 8513.32 7570.60 7524.73
  Max 9229.50 9165.59 8723.81 8441.30 8529.89
  STD 305.74 603.68 95.95 314.67 337.52
 VM200-PM100
  Min 8236.32 7397.86 8111.96 7614.16 7516.34
  Max 8995.71 8773.76 8731.38 8715.56 8756.34
  STD 205.42 472.11 244.68 275.83 401.91