  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%.
