Leveraging Computational Reuse for Cost- and QoS-Efficient Task Scheduling in Clouds

  • Chavit DenninnartEmail author
  • Mohsen Amini SalehiEmail author
  • Adel Nadjaran ToosiEmail author
  • Xiangbo LiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11236)


Cloud-based computing systems could get oversubscribed due to budget constraints of cloud users which causes violation of Quality of Experience (QoE) metrics such as tasks’ deadlines. We investigate an approach to achieve robustness against uncertain task arrival and oversubscription through smart reuse of computation while similar tasks are waiting for execution. Our motivation in this study is a cloud-based video streaming engine that processes video streaming tasks in an on-demand manner. We propose a mechanism to identify various types of “mergeable” tasks and determine when it is appropriate to aggregate tasks without affecting QoS of other tasks. Experiment shows that our mechanism can improve robustness of the system and also saves the overall time of using cloud services by more than 14%.


Task aggregation Oversubscription Cloud computing Video stream processing Task scheduling 



This research was supported by the Louisiana Board of Regents under grant number LEQSF(2016-19)-RD-A-25.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of Computing and InformaticsUniversity of Louisiana at LafayetteLafayetteUSA
  2. 2.Faculty of Information TechnologyMonash UniversityMelbourneAustralia
  3. 3.Brightcove Inc.ScottsdaleUSA

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