LBMM: A Load Balancing Based Task Scheduling Algorithm for Cloud

  • Yong ShiEmail author
  • Kai Qian
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 70)


As one of the fields in Computer Science research, Cloud Computing has attracted attentions from industries as well as academia in recent years. Numerous topics have been studied related to Cloud Computing, and one of them is task scheduling. Task scheduling is the strategy to assigning various tasks to certain resources. Existing task scheduling algorithms include Min-Min, Suffrage, Max-Min and many more, in which Max-Min is efficient in minimizing the completion time of tasks and producing a good task schedule, however, it has a drawback of load unbalancing. To address this issue, we design an algorithm called LBMM for task scheduling considering load balancing as the key concept. We conduct our experiments using CloudSim package which is a framework for simulating activities in the Cloud systems. The experimental results demonstrate that our algorithm decreases the completion time and improves load balancing of resources, and it outperforms the traditional Max-Min and Min-Min.


Task scheduling Load balancing Cloud computing Max-Min algorithm Cloud simulation 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceKennesaw State UniversityMariettaUSA

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