# Structure-Aware Scheduling Methods for Scientific Workflows in Cloud
## 4 Algorithmic Solutions
### Hierarchy-Based Approach
#### 4.2.2 Resource Allocation
Overall, the results demonstrated that the proposed algorithms outperformed the benchmarked algorithms for makespan and execution cost in most scenarios. The HBA can be extended further to address situations where hardware failure is expected to occur. The simplest mechanism to address such situations is to calculate the percentage of hardware failure for each group. Such a calculation can be based on the structure of each group and the expected execution time for the workflow tasks. Based on the calculated percentage, the weight of each group can be adjusted to capture the requirements of adding additional VMs to address the expected hardware failure. Formal analysis, A.A., F.Y., K.A. and N.M.M.N. ; Methodology, A.A., K.A. and N.M.M.N. ; Validation, A.A., F.Y. and K.A. ; Supervision, F.Y., K.A. and N.M.M.N. ; Writing--original draft, A.A.; Writing--review & editing, K.A. and N.M.M.N. All authors have read and agreed to the published version of the manuscript. This research received no external funding

Data Availability StatementData sharing is not applicable since no new data are created during this study. The authors declare no conflict of interest. Figure 6: Montage workflow experiment results. (a) makespan \((s)\); (b) cost \((e)\). Figure 7: SIPHT workflow experiment results. (a) makespan \((s)\); (b) cost \((e)\). ## References

* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON] Improved many-objective particle swarm optimization algorithm for scientific workflow scheduling in cloud computing. _Comput. Ind. Eng._**2020**, _147_, 106649. [CrossRef]
* [PERSON] et al. (2021) [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON] A hybrid multi-objective metaheuristic optimization algorithm for scientific workflow scheduling. _Clust. Comput._**2021**, _24_, 1479-1503. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON]. Scheduling Scientific Workflow Using Multi-Objective Algorithm With Fuzzy Resource Utilization in Multi-Cloud Environment. _IEEE Access_**2020**, \(8\), 24309-24322. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] A hybrid evolutionary algorithm for task scheduling and data assignment of data-intensive scientific workflows on clouds. _Future Gener. Comput. Syst._**2017**, _76_, 1-17. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON] Hybrid scheduling for scientific workflows on hybrid clouds. _Comput. Netw._**2020**, _181_, 107438. [CrossRef]
* [PERSON] and [PERSON] (2016) [PERSON]; [PERSON] Partitioning-Based Workflow Scheduling in Clouds. In Proceedings of the 2016 IEEE 30 th International Conference on Advanced Information Networking and Applications (AINA), Crans-Montana, Switzerland, 23-25 March 2016; pp. 645-652. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON] Toward Cost Efficient Cloud Bursting. In _Service-Oriented Computing, Proceedings of the 17 th International Conference, ICSOC 2019, Toulouse, France, 28-31 October 2019;_ [PERSON], [PERSON], [PERSON], [PERSON]; Springer International Publishing: Cham, Switzerland, 2019; pp. 299-313. * [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] Resource demand aware scheduling for workflows in clouds. In Proceedings of the 2017 IEEE 16 th International Symposium on Network Computing and Applications (NCA), Cambridge, MA, USA, 30 October 2017; pp. 1-5. [CrossRef]
* [PERSON] et al. (2013) [PERSON]; [PERSON]; [PERSON] Deadline-constrained workflow scheduling algorithms for Infrastructure as a Service Clouds. _Future Gener. Comput. Syst._**2013**, _29_, 158-169. [CrossRef]
* [PERSON] et al. (2002) [PERSON] [PERSON]; [PERSON]; [PERSON] Performance-effective and low-complexity task scheduling for heterogeneous computing. _IEEE Trans. Parallel Distrib. Syst._**2002**, _13_, 260-274. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Algorithms for cost- and deadline-constrained provisioning for scientific workflow ensembles in IaaS clouds. _Future Gener. Comput.