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. 2023 Feb 4;23(4):1752. doi: 10.3390/s23041752
T Task group Xi,j Population
m Count of fogs Xp Location of the target
v Number of virtual machines r1→ and r2→ Randomly selected vectors between [0, 1]
n Count of VMs α Best search agent
m Count of fogs β 2nd best optimal solution
x Count of consumers on fog F1 δ 3rd best optimal solution
u Fixed factor xα→, xβ→ and xδ→ Optimal solutions achieved in the tth iteration
β Per GB transferring price Dα Position of the α search agent
Pij Length of task Dβ Position of the β search agent
Ai Task specified for every request Dδ Position of the δ search agent
ArrivalTime The time when the task began F Scaling factor
FinishTime The time when the task execution is finished v Mutant vectors
DelayTime Delay time from customer transmitting the request till the task began to execute Max. iter Maximal number of iterations
CostDT Cost of DT POP Whole population
CostVM Cost of VM h Whole time intervals
CostMG Cost of MG CR Crossover factor
VMfinal time The final time of VM u Mutant vector
VMInitialTime Start time of VM μ Test vector
DataUsed Transmitted data which is used to execute x Target vector
TotalTime The overall time of VM D All counts of devices
Pij Length of task A and C Fitness coefficients
Kminimizw Minimizing response time and processing X Location of the wolf for the tth iteration
EXCvm1(F1) Working time of performing the group of tasks on fog F1 on VM1 a Graded from two to zero in all iterations
F1 Group of clusters of consumers PT Processing time
StartTime The start time of VM execution RT Time duration from when a request of uses is sent to fog and when a response has been obtained
FinishTime The finish time of VM execution VM Virtual machines
lj and uj Lower and upper bounds