SC is the International Conference for
High Performance Computing, Networking,
Storage and Analysis

SCHEDULE: NOV 12-18, 2011

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Auto-Scaling to Minimize Cost and Meet Application Deadlines in Cloud Workflows

SESSION: Scheduling and Resource Allocation


TIME: 2:30PM - 3:00PM

AUTHOR(S):Ming Mao, Marty Humphrey


A goal in cloud computing is to allocate only those cloud resources that are truly needed. To date, cloud practitioners have pursued schedule-based and rule-based mechanisms to attempt to automate this matching between computing requirements and computing resources. However, most of these “auto-scaling” mechanisms only support simple resource utilization indicators and do not specifically consider both user performance requirements and budget concerns. In this paper, we present an approach whereby the basic computing elements are virtual machines (VMs) of various sizes/costs, jobs are specified as workflows, users specify performance requirements by assigning (soft) deadlines to jobs. The goal is to ensure all jobs are finished within their deadlines at minimum financial cost. We accomplish our goal by dynamically allocating/deallocating VMs and scheduling tasks on the most cost-efficient instances. We evaluate our approach in four representative cloud workload patterns and show cost savings from 9.8% to 40.4% compared to other approaches.

Chair/Author Details:

Ming Mao - University of Virginia

Marty Humphrey - University of Virginia

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The full paper can be found in the ACM Digital Library

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