Modelling and Analysis of A Novel Deadline-Aware Scheduling Scheme for Cloud Computing Data Centers - 2018


User request (UR) service scheduling could be a process that considerably impacts the performance of a cloud data center. This is particularly true since essential quality-of-service (QoS) performance metrics like the UR blocking likelihood furthermore the info center's response time are tightly coupled to such a method. This Project revolves round the proposal of a novel Deadline-Aware UR Scheduling Theme (DASS) that has the objective of improving the information center's QoS performance in term of the higher than-mentioned metrics. A minority of existing work within the literature targets the formulation of mathematical models for the aim of characterizing a cloud knowledge center's performance. As a contribution to covering this gap, this Project presents an analytical model, which is developed for the aim of capturing the system's dynamics and evaluating its performance when operating below DASS. The model's results' accuracy are verified through simulations. Also, the performance of the information center achieved beneath DASS is compared to its counterpart achieved underneath the more generic 1st-In-Initial-Out (FIFO) theme. The reported results indicate that DASS outperforms FIFO by 11 to fifty eight percent in terms of the blocking likelihood and by 82 to 89 p.c in terms of the system's response time.

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