Research Area:  Cloud Computing

Abstract:

In this paper, we introduce a model of task scheduling for a cloud-computing data center to analyze energy-efficient task scheduling. We formulate the assignments of tasks to servers as an integer-programming problem with the objective of minimizing the energy consumed by the servers of the data center. We prove that the use of a greedy task scheduler bounds the constraint service time whilst minimizing the number of active servers. As a practical approach, we propose the most-efficient-server-first task-scheduling scheme to minimize energy consumption of servers in a data center. Most-efficient-server-first schedules tasks to a minimum number of servers while keeping the data-center response time within a maximum constraint. We also prove the stability of most-efficient-server-first scheme for tasks with exponentially distributed, independent, and identically distributed arrivals. Simulation results show that the server energy consumption of the proposed most-efficient-server-first scheduling scheme is 70 times lower than that of a random-based task-scheduling scheme.

Keywords:  

Author(s) Name:  Ziqian Dong, Ning Liu & Roberto Rojas-Cessa

Publisher name:  Springer

DOI:  10.1186/s13677-015-0031-y

Volume Information:  volume 4, Article number: 5 (2015)

Paper Link:   https://journalofcloudcomputing.springeropen.com/articles/10.1186/s13677-015-0031-y