An Optimal Power Management for Stationary Multiprocessor Systems

Power consumption has become a critical issue in designing computer systems. Dynamic power management is an approach that aims to reduce power consumption at system level by selectively placing components into low power states. In this paper, a power management for multiprocessor systems is proposed to optimally reduce the power consumption of processors. The key feature of the proposed power management is that sleep tasks, virtual tasks that merely switch processors into low power states, are generated and injected into the original task traffic in advance. High priorities are given to real tasks and sleep tasks are serviced only on necessity. In order to avoid unnecessary state transfers, no preemption is allowed. The goal is to appropriately switch idle processors into low power states and meanwhile minimize the average response time of real tasks. A probabilistic policy towards the goal is also introduced. The analysis of the probabilistic policy is based on such an queueing model: there are multiple processors and a global queue, the system is in equilibrium, i.e. a stationary traffic and a stable queue, except two priorities tasks are same and non-preemptive. Based on the queueing model, the optimality of the proposed power management is discussed and analyzed.