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