Khazar University

12 March, 2025Joint Article by Mathematics Department Professors Published in "Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes" Journal

20 February, 2025Mathematics Department Professor's Article Published in "Filomat" Journal

08 January, 2025Mathematics Department Professors' Joint Article Published in "Applicable Analysis and Discrete Mathematics" Journal

05 December, 2024Joint Article by Mathematics Department Professors Published in "Sahand Communications in Mathematical Analysis"

20 November, 2024Book by Head of Political Science and Philosophy Department Published in Persian in Iran

Article by Khazar University scholar published in International Scientific Journal

An article entitled “TMaR: a two-stage MapReduce scheduler for heterogeneous environments”, co-authored by Dr. Amir Rahmani, Professor of Computer Science at Khazar University was published by Springer publisher, in Human-centric Computing and Information Sciences journal.

In the context of MapReduce task scheduling, many algorithms mainly focus on the scheduling of Reduce tasks with the assumption that scheduling of Map tasks is already done. However, in the cloud deployments of MapReduce, the input data is located on remote storage which indicates the importance of the scheduling of Map tasks as well. In this paper, we propose a two-stage Map and Reduce task scheduler for heterogeneous environments, called TMaR. TMaR schedules Map and Reduce tasks on the servers that minimize the task finish time in each stage, respectively. The simulation results demonstrate that TMaR outperforms Hadoop-stock and Hadoop-A in terms of makespan and network traffic and achieves by an average of 29%, 36%, and 14% performance using Wordcount, Sort, and Grep benchmarks. Besides, the power reduction of TMaR is up to 12%.

The article can be found at this link:

https://hcis-journal.springeropen.com/articles/10.1186/s13673-020-00247-5