Algorithm 1. STaSA

Input: p; Max_Loop; Ants_N; Q; $\beta ,\gamma ,\rho ;{\phi }_1;$ $tim{e}_j$; $v_{mem}^{f,t}$, $v_{cpu}^{f,t}$ $e_n$.

Output: Placement of pod i on node j

1: Initialize parameters $\{Max\text{\_}Loop,Ants\text{\_}N,Q,\alpha , \beta , \gamma ,\rho$}

2: If $(v_{cpu}^{f,t}+v_{mem}^{f,t}>R)$ then

Instantiate new set of nodes using Equation (7)

//include check capacity condition of nodes states

3: End if

4: Initialize the pheromone trail using Equation (13)

5: Initialize the placement cost using Equation (9)

6: For nloop from 1 to Max_Loop do

7:   Random shuffle input pod queue

8:    For ant_k from 1 to Ants_N do

9:     For i from 1 to p do

10:      Calculate the time value based on (12)

11:      Calculate the probability of placement of pod i on each node j using

12:       Equation (13)

//ant_k chooses node j for pod i according to the highest probability

Add the selected node j to the schedule table as a placement of pod i for ant_k

13:     End for

14:     Calculate the cost of pod i for ant_k using Equation (10)

15:    End for

16:   Update the pheromone trail using Equation (15)

17:  End for

18: Repeat until the maximum number of iterations is reached or best placement found