Load Balancing For Cloud-Based Dynamic Data Processing
Talal Talib Jameel
DOI : 10.3844/jcssp.2017.301.306
Journal of Computer Science
Volume 13, Issue 8
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.
© 2017 Talal Talib Jameel. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.