Abstract
SummaryPerformance and power are 2 significant issues in cloud computing. It is a critical issue on how to provide the best quality of service by consuming certain available power resource. For a given application environment and a given group of servers, optimal load distribution and optimal server speed setting can be an effective way to deal with the power‐performance tradeoff. The technique of variable and task‐type–dependent server speed management can be explored to optimize the server performance and to minimize the power consumption of a server with mixed applications. In this paper, we consider the problem of optimal load distribution for multiple classes of applications on heterogeneous servers with variable speeds. Given several classes of applications characterized by their arrival rates and expected execution requirements, several heterogeneous servers characterized by their power consumption parameters, and certain power supply, our problem is formulated as a multivariable optimization problem, ie, finding an optimal load distribution and an optimal server speed setting, such that the average task response time is minimized. To study the problem analytically, each server is treated as an M/G/1 queueing system with mixed classes of tasks such that both the average response time and the average power consumption can be calculated analytically. We define a power constrained performance optimization problem and develop a numerical algorithm to solve our optimization problem by solving a system of nonlinear equations. We also demonstrate numerical examples to show the effectiveness of our model and method. To the best of our knowledge, such analytical study of optimal load distribution and optimal server speed setting for multiple classes of applications on heterogeneous servers with variable speeds has not been available in the existing literature.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.