Overview
Abdelkhalik, known as Abdo, is a Senior Lecturer (E&S) in the Department of Computer Science. I obtained my PhD and MSc in Computer Science from the University of Manchester in 2019 and 2014, respectively. I am also a Fellow of the Higher Education Academy (FHEA).
I am experienced in designing, developing and delivering innovative computer science curricula and assessments. In addition, I have extensive teaching experience in programming languages (e.g. Java, Python, JavaScript and PHP), web and cross-platform mobile development, computer networks, cyber security, databases, big data analytics, distributed systems and cloud computing.
My research expertise is in creating self-managing distributed systems, with a particular emphasis on the autonomic provisioning and management of cloud and edge infrastructures. My work includes exploring the automatic scalability and auto-deployment of containerised applications, such as big data platforms, in the cloud utilising both reactive and proactive machine learning approaches. Research interests include:
- Resource management in Cloud and Edge Computing
- Auto-scaling and deployment of containerised applications in the Cloud
- Scheduling algorithms in distributed systems
- Scalable big data infrastructures
- Machine learning for proactive resource management and provisioning
I have contributed to EU-funded projects, notably during my postdoctoral research position at the University of Westminster, where I worked on the COLA project. This project resulted in the development of MiCADO, an open-source, highly adaptable multi-cloud orchestration and auto-scaling framework for Docker containers, managed by Kubernetes. I also participated in the RABBDA project, a research collaboration between the University of Westminster and Westminster International University in Tashkent, which aimed to make big data analytics tools more accessible. In addition, I am a reviewer for several Computer Science journals, including the Journal of Grid Computing, IEEE Transactions on Cloud Computing, and the Journal of Cloud Computing.
Publications
Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.
| 2020 | 2019 | 2018 | 2017 | 2016 |
2020
- Kiss T, Bolotov A, Pierantoni G, Deslauriers J, Mosa A, Kagialis D, Terstyanszky G, Chan You Fee D. (2020) Science Gateways with Embedded Ontology-based E-learning Support, 12th International Workshop on Science Gateways, Online, 10th - 11th Jun 2020.
- Mosa A, Kiss T, Pierantoni G, DesLauriers J, Kagialis D, Terstyanszky G. (2020) Towards a Cloud Native Big Data Platform using MiCADO, 2020 19TH INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED COMPUTING (ISPDC 2020), pages 118-125, DOI:10.1109/ISPDC51135.2020.00025. [PDF]
2019
- Mosa A. (2019) Virtual Machine Consolidation in Cloud Data Centres using a Parameter-based Placement Strategy.
- Mosa A, Sakellariou R. (2019) Dynamic Virtual Machine Placement Considering CPU and Memory Resource Requirements, 2019 IEEE 12TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (IEEE CLOUD 2019), pages 196-198, DOI:10.1109/CLOUD.2019.00042. [PDF]
2018
- Mosa A, Sakellariou R. (2018) Dynamic Tuning for Parameter-based Virtual Machine Placement, 2018 17TH INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED COMPUTING (ISPDC), pages 38-45, DOI:10.1109/ISPDC2018.2018.00015. [PDF]
2017
- Mosa A, Sakellariou R. (2017) Virtual Machine Consolidation for Cloud Data Centers Using Parameter-Based Adaptive Allocation, PROCEEDINGS OF THE FIFTH EUROPEAN CONFERENCE ON THE ENGINEERING OF COMPUTER-BASED SYSTEMS (ECBS 2017), DOI:10.1145/3123779.3123807. [PDF]
2016
- Mosa A. (2016) Autonomic Virtual Machine Management in Cloud Data Centers.
- Mosa A, Paton NW. (2016) Optimizing virtual machine placement for energy and SLA in clouds using utility functions, JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, volume 5, article no. ARTN 17, DOI:10.1186/s13677-016-0067-7. [PDF]
