# Constructing Reliable Computing Environments on Top of Amazon EC2 Spot Instances +
## 5 Results and Analysis
MW-DBS-O is able to successfully complete more than 97.5% of workflows, decreasing its performance as spot resources become part of the schedules. In truth, the performance of MW-DBS-OB slightly improves as the deadline increases, varying between 54.2% (\(D=1.0\) and \(B=0.25\)) and 63.6% (\(D=1.5\) and \(B=0.50\)). As for the *-OBS resources and MW-DBS combination, the strategy completed between \(\sim\)62% and \(\sim\)65% of workflows. Similarly to the case of task efficiency, ECPTR performs better than MW-DBS for high deadlines (i.e., \(D=1.5\)). MISER showed itself to be able to maintain the completion rate of workflows at 100% for almost all cases, even when tasks were allocated on spot resources. The planning efficiency is shown in Figure 2c. Here, the objective was to analyze the success rate of finding a valid schedule map for each workflow task in the scenario considering deadline and budget constraints. MISER proved to be stable in finding task-to-instance mappings, successfully scheduling 100% of the tasks for all considered budget and deadline constraints, and for all possible *-OBS, *-OB, and *-O configurations. What is more, MISER-OBS outperformed MW-DBS-OBS and ECPTR-OBS by as much as 16.3% and 15.6%, respectively. The ECPTR-O* performances fell from 100% of planning efficiency to 84.4% for *-OBS (\(D=1.0\) and \(B=0.50\)). Here, the same pattern was observed: ECPTR performance (a) improved with increasing deadline; and (b) beat the performance of MW-DBS for  
Figure 2: The performance of the scheduling algorithm and container-based migration strategy in terms of: (**a**) Task efficiency \(E_{T}\). (**b**) Workflow efficiency \(E_{W}\). (**c**) Planning efficiency \(E_{P}\). (**d**) \(E_{C}\), the ratio of the completion rate of tasks (or task efficiency) to the product of average task runtime and monetary costs (higher is better). high deadlines. In turn, adopting a scheduler that does not consider the nature of different instance purchasing models, as is the case of MW-DBS, leads to a planning success rate that can be as low as 83.7%, 80.8%, or 99.3 for *-OBS, *-OB, and *-O configurations, respectively. Figure 2d characterizes the performances of the scheduling algorithms in terms of completion rate of tasks, monetary costs in executing those tasks, and average task execution time. The idea is to understand how good the algorithm is at balancing all the three factors. Comparing the results obtained for all the scheduling algorithms, the best results were achieved by the MISER and *-OBS configuration. In fact, MISER was able to utilize on-demand, spot blocks, and SIs more efficiently in order to strongly reduce the average execution time, and cumulatively slightly decrease the monetary costs with rented instances while achieving a completion rate of tasks of 100%. More precisely, the average execution time of tasks and rate of completed tasks are the two factors that most contribute to the good results obtained, compared with the factor monetary costs. The second best results were obtained for MISER and *-OB configuration. Spot block instances are cheaper than on-demand instances, which allows the scheduler to chose powerful instance types and reduce the average task execution time, while not increasing the monetary costs with resources. Regarding MW-DBS, it performs better with on-demand instances (i.e., for *-O configuration) if compared to *-OBS and *-OB configurations, due to two factors: (a) higher completion rate of tasks; and (b) lower average execution times. Similarly, ECPTR performs better with *-O and *-OB than with *-OBS configuration because of: (a) the lower average execution times; and (b) the higher completion rate of tasks. Figure 3 identifies the number of schedules per instance pricing model, aiming at describing the instance purchasing models by which workflow tasks were scheduled. It is evident that all algorithms show a preference for resources of lower monetary cost (excepting the case of ECPTR-OB configuration, which is unable to manage spot block resources).