@article {10.3844/jcssp.2017.301.306,
article_type = {journal},
title = {Load Balancing For Cloud-Based Dynamic Data Processing},
author = {Jameel, Talal Talib},
volume = {13},
number = {8},
year = {2017},
month = {May},
pages = {301-306},
doi = {10.3844/jcssp.2017.301.306},
url = {https://thescipub.com/abstract/jcssp.2017.301.306},
abstract = {The Map/Reduce paradigm has dominated cloud computing since its beginnings. However, there are some scenarios in which Map/Reduce is not the best model. Once such situation is a system that collects data dynamically, with intermittent arrival times. In this study, we study a modified form of Map/Reduce that uses a load balancer to distribute work, rather than simply assigning a Map node in an ad-hoc fashion. We show that this approach performs significantly better than standard Map/Reduce. In particular, it reduces the amount of time data is waiting in a queue to be processed.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}