ScholarWorks@숙명여자대학교

초록

Cloud computing platform is becoming one of the most desired environments for the emerging applications as well as traditional application domains. In this regards, there have been lots of efforts to develop and redesign the framework to deliver solutions that meet a variety of requirements including resilience, performance, and agility. This paper presents a design and implementation of iSDF, an integrated software-defined computing framework for scientific experiments. The iSDF aims at reinforcing traditional cloud-based scheme by supporting application-Aware scheduling that avoids resource starvation and contentions for software-defined computing. To demonstrate the effectiveness of the iSDF, we evaluate it by performing several experiments based on three scenarios. The results show that our framework can achieve a 51% increase on resource utilization and average makespan time a 19% improvement compared to the conditions that do not include the policy. Thus, we proved that the framework can contribute to increase utilization for shared resources and to optimize overall makespan time, eventually affecting overall throughput of jobs. © 2017 IEEE.

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