Dr. E.N.M. (Ehab) Al-Khannaq
I completed my degree in Computer Sciences in 2005. Then, I pursued a Master’s degree in Computer Sciences from the University of Malaya (UM) in 2009. I have also completed my PhD. from the same university. I have worked as a Web-developer for more than two years; thereafter I worked as a Research Assistant for four years. After that I worked as a NOC Engineer and my recent position was a lecturer at HELP University.
I have published several ISI-cited papers and my research interests are big data, cloud computing, scientific workflow application, meta-heuristic methods, and web-services. I am currently working on Multiscale integrated traffic observatory for large road networks (MiRRORS) project and my main responsibility is to develop the big data and computing solutions.
Ehab Nabiel Alkhanak, Sai Peck Lee, A Hyper-Heuristic Cost Optimisation Approach for Scientific Workflow Scheduling in Cloud Computing, Future Generation Computer Systems (2018).
Ehab Nabiel Alkhanak, Sai Peck Lee, Reza Rezaei, Reza Meimandi Parizi. “Cost optimization approaches for scientific workflow scheduling in cloud and grid computing: A review, classifications, and open issues”, Journal of Systems and Software (2016), Volume 113, Pages 1-26, ISSN 0164-1212.
Ehab Nabiel Alkhanak, Sai Peck Lee, Saif Ur Rehman Khan, Cost-aware challenges for workflow scheduling approaches in cloud computing environments: Taxonomy and opportunities, Future Generation Computer Systems (2015), Volume 50, September 2015, Pages 3-21, ISSN 0167-739X.
MiRRORS - Multiscale integrated traffic observatory for large road networks
In this project, we develop a new innovative multi-scale framework that can deliver these for large road traffic networks using whatever data sources are available. Our approach is unique in the world. First, we develop hybrid approaches where we combine pattern recognition and classification approaches with state-of-the-art traffic flow models. Second, we develop integrated multi-scale solutions, in which traffic information we estimate on one scale level is used to support and strengthen estimation and prediction on other levels. Third, we develop a distributed approach that is robust and scalable for large-scale road networks.
Ehab Nabiel Alkhanak, and Salimah Mokhtar. "Delivery of Service Oriented Architecture with Web Services.", Amazon (2012).