Dr Maria Rodriguez Sossa

  • Room: Level: 03 Room: 27
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Cloud computing
  • Distributed Systems
  • Parallel Computing
  • Scientific Computing

Biography

Dr. Maria Rodriguez is a Lecturer in the School of Computing and Information Systems. Her research interests lie in the field of distributed and parallel systems. Her work has focused on the efficient orchestration of scientific applications in cloud environments and includes topics such as scheduling, resource provisioning, task runtime prediction, and performance anomaly detection. She has also built various frameworks that enable the practical application of her research. More recently, she has worked on investigating how containerized and cloud-native applications can be better supported by cloud providers to offer users advantages in terms of reduced cost and more scalable, robust, and flexible application deployment.

Recent publications

  1. Buyya, R.; Srirama, SN.; Casale, G.; Calheiros, R.; Simmhan, Y.; Varghese, B.; Gelenbe, E.; Javadi, B.; Vaquero, LM.; Netto, MAS.; Toosi, AN.; Rodriguez, MA.; Llorente, IM.; Di Vimercati, SDC.; Samarati, P.; Milojicic, D.; Varela, C.; Bahsoon, R.; De Assuncao, MD.; Rana, O.; Zhou, W.; Jin, H.; Gentzsch, W.; Zomaya, AY.; Shen, H. A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade. ACM Computing Surveys. ASSOC COMPUTING MACHINERY. 2019, Vol. 51, Issue 5. DOI: 10.1145/3241737
  2. Rodriguez, MA.; Buyya, R. Container-based cluster orchestration systems: A taxonomy and future directions. Software: Practice and Experience. WILEY. 2019, Vol. 49, Issue 5, pp. 698-719. DOI: 10.1002/spe.2660
  3. Buyya, R.; Rodriguez, MA.; Toosi, AN.; Park, J. Cost-Efficient Orchestration of Containers in Clouds: A Vision, Architectural Elements, and Future Directions. Journal of Physics: Conference Series. Atlantis Press. 2018, Vol. 1108, Issue 1, pp. 012001-012001. DOI: 10.1088/1742-6596/1108/1/012001
  4. Rodriguez, MA.; Kotagiri, R.; Buyya, R. Detecting performance anomalies in scientific workflows using hierarchical temporal memory. Future Generation Computer Systems. ELSEVIER SCIENCE BV. 2018, Vol. 88, pp. 624-635. DOI: 10.1016/j.future.2018.05.014
  5. Rodriguez, MA.; Buyya, R. Scheduling dynamic workloads in multi-tenant scientific workflow as a service platforms. Future Generation Computer Systems. ELSEVIER SCIENCE BV. 2018, Vol. 79, pp. 739-750. DOI: 10.1016/j.future.2017.05.009
  6. Hilman, MH.; Rodriguez, MA.; Buyya, R. Task Runtime Prediction in Scientific Workflows Using an Online Incremental Learning Approach. 2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC). IEEE. 2018, pp. 93-102. DOI: 10.1109/UCC.2018.00018
  7. Rodriguez, MA.; Buyya, R. A taxonomy and survey on scheduling algorithms for scientific workflows in IaaS cloud computing environments. Concurrency and Computation: Practice and Experience. WILEY. 2017, Vol. 29, Issue 8. DOI: 10.1002/cpe.4041
  8. Rodriguez, MA.; Buyya, R. Budget-Driven Scheduling of Scientific Workflows in IaaS Clouds with Fine-Grained Billing Periods. ACM Transactions on Autonomous and Adaptive Systems. ASSOC COMPUTING MACHINERY. 2017, Vol. 12, Issue 2. DOI: 10.1145/3041036
  9. Rodriguez, MA.; Buyya, R. SCIENTIFIC WORKFLOW MANAGEMENT SYSTEM FOR CLOUDS. . MORGAN KAUFMANN PUB INC. 2017, pp. 367-387. DOI: 10.1016/B978-0-12-805467-3.00018-1
  10. Hilman, MH.; Rodriguez, MA.; Buyya, R. Task-based Budget Distribution Strategies for Scientific Workflows with Coarse-grained Billing Periods in IaaS Clouds. 2017 IEEE 13th International Conference on e-Science (e-Science). IEEE. 2017, pp. 128-137. DOI: 10.1109/eScience.2017.25
  11. Rodriguez, MA.; Buyya, R. A Responsive Knapsack-Based Algorithm for Resource Provisioning and Scheduling of Scientific Workflows in Clouds. 2015 44th International Conference on Parallel Processing. IEEE. 2015, Vol. 2015-December, pp. 839-848. DOI: 10.1109/ICPP.2015.93
  12. Rodriguez, MA.; Buyya, R. Deadline Based Resource Provisioningand Scheduling Algorithm for Scientific Workflows on Clouds. IEEE Transactions on Cloud Computing. Institute of Electrical and Electronics Engineers (IEEE). 2014, Vol. 2, Issue 2, pp. 222-235. DOI: 10.1109/TCC.2014.2314655