|
|
Task group |
|
Population |
|
|
Count of fogs |
|
Location of the target |
|
|
Number of virtual machines |
and
|
Randomly selected vectors between [0, 1] |
| n |
Count of VMs |
|
Best search agent |
| m |
Count of fogs |
|
2nd best optimal solution |
|
|
Count of consumers on fog
|
|
3rd best optimal solution |
|
|
Fixed factor |
, and
|
Optimal solutions achieved in the iteration |
|
|
Per GB transferring price |
|
Position of the search agent |
|
|
Length of task |
|
Position of the search agent |
|
|
Task specified for every request |
|
Position of the search agent |
|
|
The time when the task began |
|
Scaling factor |
|
|
The time when the task execution is finished |
|
Mutant vectors |
|
|
Delay time from customer transmitting the request till the task began to execute |
Max. iter |
Maximal number of iterations |
|
|
Cost of DT |
|
Whole population |
|
|
Cost of VM |
|
Whole time intervals |
|
|
Cost of MG |
|
Crossover factor |
|
|
The final time of VM |
|
Mutant vector |
|
|
Start time of VM |
|
Test vector |
|
|
Transmitted data which is used to execute |
|
Target vector |
|
|
The overall time of VM |
D |
All counts of devices |
|
|
Length of task |
A and C |
Fitness coefficients |
|
|
Minimizing response time and processing |
X |
Location of the wolf for the iteration |
|
|
Working time of performing the group of tasks on fog on
|
|
Graded from two to zero in all iterations |
|
|
Group of clusters of consumers |
|
Processing time |
|
|
The start time of VM execution |
|
Time duration from when a request of uses is sent to fog and when a response has been obtained |
|
|
The finish time of VM execution |
|
Virtual machines |
|
and
|
Lower and upper bounds |
|
|