Hamzeh KhazaeiAAssociate Professor
Electrical Engineering and Computer Science Department
Electrical Engineering and Computer Science Department
Associate Professor, EECS Department
Member, IC@L
Member, Centre for Vision Research
Adjunct Professor in Electrical and Computer Engineering (ECE) @ University of Alberta
2021 – 2022 Research Highlights
Performant Serverless Computing for Private IoT Data Analysis
Serverless computing is the latest paradigm of computation in cloud computing. Users are genuinely billed for what they use and have no concern/responsibility regarding the management of back-end servers. Serverless or Function as a Service is considered the future of cloud computing, and most cloud users are expected to assume this type of services. However, the main challenge toward the wide adoption of serverless computing is related to the high variability in performance which renders it not to be quite suitable for time-sensitive workloads. In PACS lab, we strive to leverage analytical models to analyze and then design innovative platforms that can guarantee the service level agreement requirements, including performance and availability. During the year of 2020, we continue our research by proposing novel analytical models for steady-state and transient analysis of modern serverless computing systems. One of our works has been shortlisted for the best paper award in a top conference in cloud computing. Thanks to the support that we received from IC@L; we have initiated research on preserving privacy in IoT systems in collaboration with ASRL lab lead by Dr. Marin Litoiu. We hired a MSc student who is now working on this project as part of his master’s thesis. We are working on a proposal to collaborate with an industry partner, Ecobee, on privacy preserving data analysis in IoT by leveraging multi-layer serverless cloud and machine learning autoencoders. Afterward, we plan to use the IC@L, and Ecobee supports to apply for a large multi-year grant from federal or provisional agencies. Provided that, we will be able to support more graduate students to work on this exciting topic.
Research Highlights
- A. Goli, N. Mahmoudi, H. Khazaei, and O. Ardakanian, “A Holistic Machine Learning-Based Autoscaling Approach for Microservice Applications,” in The 11th International Conference on Cloud Computing and Services Science, 2021.
- N. Mahmoudi and H. Khazaei, “SimFaaS: A Performance Simulator for Serverless Computing Platforms,” in International Conference on Cloud Computing and Services Science, 2021, p. 1–11. Shortlisted for best paper award.
- O. Hajihassani, O. Ardakanian, and H. Khazaei, “ObscureNet: Learning Attribute-invariant Latent Representation for Anonymizing Sensor Data,” in In Proceedings of the 6th ACM/IEEE Conference on Internet of Things Design and Implementation, 2021.
- S. Gholami, H. Khazaei, and C. Bezemer, “Should you Upgrade Official Docker Hub Images in Production Environments?” in In Proceedings of the International Conference on Software Engineering, 2021, p. 1–5.
- C. Lin and H. Khazaei, “Modeling and Optimization of Performance and Cost of Serverless Applications,” IEEE Transactions on Parallel and Distributed Systems, vol. 32(3), pp. 615-632, 2021.
- N. Mahmoudi and H. Khazaei, “Performance Modeling of Serverless Computing Platforms,” IEEE Transactions on Cloud Computing, pp. 1-15, 2020.
- H. Khazaei, N. Mahmoudi, C. Barna, and M. Litoiu, “Performance Modeling of Microservice Platforms,” IEEE Transactions on Cloud Computing, pp. 1-15, 2020.
- N. Mahmoudi and H. Khazaei, “Temporal Performance Modelling of Serverless Computing Platforms,” in Proceedings of the 6th Int. Workshop on Serverless Computing, 2020, p. 1–6.
- C. Lin, S. Nadi, and H. Khazaei, “A Large-scale Data Set and an Empirical Study of Docker Images Hosted on Docker Hub,” in Proceedings of the 36th IEEE International Conference on Software Maintenance and Evolution (ICSME), 2020.
- S. Ghaemi, H. Khazaei, and P. Musilek, “ChainFaaS: An Open Blockchain-based Serverless Platform,” IEEE Access, 2020.
- C. Fan, S. Ghaemi, H. Khazaei, and P. Musilek, “Performance Evaluation of Blockchain Systems: A Systematic Survey,” IEEE Access, 2020.