Autonomic Cloud Management System (ACMS)

Overview

Cloud enhances cooperation, scaling, performance, and accessibility by reducing cost, improving performance and providing on-demand computing, storage and network resources that can be accessed using heterogeneous thin or thick client platforms. Power and performance management of these systems is a great challenge since power cost during the lifetime of a cloud system can be 2-3 times higher than the infrastructure cost and, also, high power consumption can cause reliability issues in long term due to hot-spots. While current high performance computing systems are designed to handle the peak workload of these systems, the workload varies greatly during runtime. As a result, many studies have shown that data servers typically operate at a low utilization, while their consumption of power is close to those at peak loads. Our goal is to minimize the power consumption while maintaining the high performance for Platform as a Service (PaaS) by scaling up/down the hardware resources during runtime. In this project, we are developing an autonomic power and performance management system based on "AppFlow based reasoning" where AppFlow is n-dimensional array representing workload behavior during its lifespan. In our approach, we classify the workloads into a set of workload types and for each workload type, we model the behavior. Similar to case based reasoning, the online monitoring and analysis of the workload will determine the appropriate AppFlow type to describe current workload accurately. Once determined, virtual machine resources are re-allocated according to the determined AppFlow type such that power consumption is minimized without any performance loss. Our experimental results showed that our approach can reduce the power consumption up to 84% compared to static resource allocation and up to 30% compared to other methods with minimum performance degradation.

Fig. 1 - ACM management console.


Fig. 2 - ACM architecture overview.
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People


Farah Fargo
email:
website: www2.engr.arizona.edu/~farahfarjo/


Cihan Tunc
email:
website: www.cihantunc.com


Youssif Al-Nashif
email:
website: www2.engr.arizona.edu/~alnashif/



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