Jump-start cloud: efficient deployment framework for large-scale cloud applications

  • Authors:
  • Xiaoxin Wu;Zhiming Shen;Ryan Wu;Yunfeng Lin

  • Affiliations:
  • Huawei Corporate Research, Beijing, China;Department of Computer Science, North Carolina State University, Raleigh, NC, USA;tuan800.com, Beijing, China;Intel China Research Center Ltd., Beijing, China

  • Venue:
  • Concurrency and Computation: Practice & Experience
  • Year:
  • 2012

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Abstract

Reducing the time that a user has to occupy resources for completing cloud tasks can improve cloud efficiency and lower user cost. Such a time, called cloud time, consists of cloud deployment time and application running time. In this work, we design Jump-start cloud, under which an efficient cloud deployment scheme is proposed for minimizing cloud time. It is especially beneficial to minimize cloud time for clouds serving multimedia applications, as they occupy much more significant cloud resources, such as disk I/O and networking bandwidth and computational costs in processing or transcoding multimedia contents. In particular, we have implemented virtual machine cloning based on disk image sharing for fast virtual machine and application deployment. For applications with heavy disk visits, the post-deployment QoS may suffer from image sharing, and consequently, application running time will increase. To solve this problem, different image distribution schemes have been designed. We test Jump-start cloud through a Hadoop-based benchmark and MapReduce applications. Experiment studies show that our design saves application installation time and, meanwhile, keeps application running time reasonably low, thus makes cloud time shorter. Copyright © 2011 John Wiley & Sons, Ltd.