Abstract: In recent years, real-time and big data aroused and received a lot of attention due to the spread of embedded systems in almost everything in life. This has led to many challenges that need to be solved to enhance and improve systems that work on big real-time data. Apache Storm is a system used for computing and analyzing big real-time data of distributed systems. This paper aims to develop a scheduler to improve the scheduling of the applications represented by topologies on the Storm cluster. The proposed scheduler is hybridization between the scheduling algorithms of A3 Storm and the Workload scheduler. Its objective is to minimize the communication between tasks while balancing the workload on all cluster machines. The proposed scheduler is compared with the A3 Storm and Fischer and Bernstein’s scheduling algorithm. The comparison has been made using four different topologies. The experimental results show that our proposed scheduler outperforms the two other schedulers in throughput and complete latency.

Arwa Z. Selim, Noha E. El-Attar, I. M. Hanafy and Wael A. Awad, “Balanced Schedule on Storm for Performance Enhancement” International Journal of Advanced Computer Science and Applications(IJACSA), 13(1), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130175

@article{Selim2022,
title = {Balanced Schedule on Storm for Performance Enhancement},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130175},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130175},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {1},
author = {Arwa Z. Selim and Noha E. El-Attar and I. M. Hanafy and Wael A. Awad}
}