Investigation Open Access

Load Balancing For Cloud-Based Dynamic Data Processing

Talal Talib Jameel1
  • 1 Al Yarmouk University College, Iraq


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 of Computer Science
Volume 13 No. 8, 2017, 301-306


Submitted On: 22 December 2016 Published On: 20 May 2017

How to Cite: Jameel, T. T. (2017). Load Balancing For Cloud-Based Dynamic Data Processing. Journal of Computer Science, 13(8), 301-306.

  • 1 Citations



  • Cloud Computing
  • Load Balancing
  • Map/Reduce
  • Dynamic Data
  • Resource Allocation
  • Data Center