# Secure Partitioning of Cloud Applications, with Cost Look-Ahead
## 7 Experimental Assessment
### Discussion of the Results
Our results have a minimum of \(0.87\) seconds with \(K\) and \(D\) equal to one and about 28,000 \(s\) with \(K\) and \(D\) at their maximum values, respectively, \(13\) and six._  
From the point of view of execution time, the best choice seems to be the lowest possible values for \(K\) and \(DLimit\), but we have also to consider their impact on the partitioning costs. In this regard, we now answer the question  
**Q3:**_How much do \(K\) and \(DLimit\) impact the safe partitioning costs?_  
Having a low value of \(DLimit\) reduces the choice for the starting partitioning. Figure 8 shows that having \(DLimit\) equal to four has only one partitioning satisfying the starting labelling, the minimal partitioning. Its future cost grows with \(K\) because the number of labellings to be satisfied that need a different minimal partitioning grows. The situation is more interesting with \(DLimit\) equal to five, as depicted in Figure 9, where the choice is among four partitionings. The minimal partitioning cost is less than before because when a labelling is not satisfied, the software can also be migrated to partitionings with five domains, with a lower cost than partitioning with four domains. Obviously, the orange partitioning will always be a bad choice, as it is the most costly, with five domains. The choice of the starting partitioning depends on the selected \(K\); the application operator should decide whether to minimise the number of domains--having a higher future cost--or have one more domain with a lower future cost. For example, with \(K\) equal to one, the choice is between the purple partitioning (five domains and \(0\) future cost) and the blue one (four domains and \(3.68\) future cost). The last scenario, with \(DLimit\) set to six, is depicted in Figure 10. There is one partitioning more than before, the green one, that is the partitioning where all the software components are isolated in different domains. This partitioning is always safe and always has zero future cost because there is no labelling that forces migration of the software components, but it has the highest number of domains. For applications with a high number of software components, it is not affordable to isolate all the components and also, in this example, it is not the best choice. The red partitioning has one domain less and the same zero future cost. This happens because changing the partitioning from the red one to the green one has zero cost, so labellings that are not satisfied by the red partitioning are enough to migrate the software to the green one, increasing the number of domains but without paying an additional cost in working on the software communication. The idea behind the choice of the starting partitioning is the same as before: once \(K\) is picked, the application operator should decide how many domains to use at the start, knowing that the migration could require up to six domains to have the minimal cost. In conclusion, having a low value of \(K\) brings lower future costs because the probability of reaching an unsatisfiable labelling is less. Instead, having a low value of \(DLimit\) brings higher future costs because there is less choice for the starting partitioning and for the migration. In summary, _fixing \(DLimit\) equal to four, the future cost of the minimal partitioning is \(6.8\) work hours, the lowest value, when \(K\) is equal to one. As \(K\) grows over seven the future cost is stabilised at about \(16.1\) work hours. Fixing \(DLimit\) equal to five, the future cost of the minimal partitioning is \(3.7\) work hours, the lowest value, when \(K\) is equal to one. As \(K\) grows over seven the future cost is stabilised at about \(14.8\) work hours. For partitioning with five domains, the behaviour depends on the application architecture and we record as the minimum future cost \(0\) work hourswith K equal to one and 2.7 with K equal to \(13\). Finally, fixing DLimit equal to six, the future cost of the minimal partitioning is 3.7 work hours, the lowest value, when K is equal to one.