Work place: Institute of Information Technology/Azerbaijan National Academy of Sciences, Baku, AZ1141, Azerbaijan
Research Interests: Cloud Computing, Computer Networks
Rashid G. Alakbarov graduated from Automation and Computer Engineering faculty of Azerbaijan Polytechnic University named after C. Ildirim. He received his PhD degree in 2006 from Supreme Attestation Commission under the President of the Republic of Azerbaijan. His primary research interests include various areas in cloud computing, data processing, computer networks, virtual computing, particularly in the area of distributed computing. He is head of department at the Institute of Information Technology as of 2002. Since 2010, he has been leading the development of “AzScienceNet” infrastructure. In 2021, he was appointed an executive director of the institute by the decision of the Presidium of Azerbaijan National Academy of Sciences. He is the author of 95 scientific papers, including 5 inventions.
DOI: https://doi.org/10.5815/ijcnis.2023.05.02, Pub. Date: 8 Oct. 2023
In traditional mobile cloud computing, user tasks are uploaded and processed on a cloud server over the Internet. Due to the recent rapid increase in the number of mobile users connected to the network, due to overload of the Internet communication channels, there are significant delays in the delivery of data processed on cloud servers to the user. Furthermore, it complicates the optimal scheduling of the tasks of many users on cloud servers and the delivery of results. Scheduling is an approach used to reduce the tasks execution time by ensuring a balanced distribution of user tasks on cloud servers. The goal of scheduling is to ensure selection of appropriate resources to handle tasks quickly, taking into account user requirements. Whereas the goal of cloud service providers is to provide users with the required resources through performing effective scheduling so that both the user and the service provider can benefit. The article proposes a scheduling model to reduce processing time, network latency, and power consumption of mobile devices through optimal task placement in the cloudlet network in a mobile cloud computing environment.[...] Read more.
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