Power-aware scheduling in computing and communications with QoS requirements

Driven by the demand for higher computational power and communication capabilities, the power consumption of electronic computing devices has increased drastically in the past decade. This calls for innovative and more energy efficient system designs not only for battery-powered portable devices but also for computer servers and server clusters that face the overheating problem. The concept of power-awareness has been incorporated into today's hardware and software development as an important design criteria.; This thesis studies the use of software strategies to improve energy efficiency in computing and wireless communications. In particular, we investigate the impact of scheduling on power management and propose new strategies for processor scheduling and wireless data transmission/reception to improve energy efficiency without violating the QoS requirements of the applications.; We first address the issue of power-aware voltage scaling for real-time periodic tasks. The concept of "blocking-awareness" is introduced in the context of scheduling tasks with non-preemptible sections. The proposed blocking-aware algorithms dynamically adjust the processor speed based on run-time blocking occurrences instead of worst-case blocking expectation, therefore they can greatly reduce processor energy consumption over static speed schemes.; The workload of desktop PCs and server systems is usually aperiodic and an average delay guarantee is desirable. We design stationary voltage scaling policies that adjust the processor speed according to the number of tasks in the system. Markov models are employed to compute the statistically energy-optimal policy. This approach is then extended to multiprocessor systems and heterogeneous server clusters, where some processors are selectively turned off to further reduce energy dissipation.; The wireless transceiver is another major energy consumer in a networked computer system. For wireless networks with limited energy and a designed lifetime, it is important to maximize the utility of available energy instead of minimizing energy usage. We present an iterative algorithm to compute the optimal transmission power setting to multiple receivers. The transmission schedule produced fully utilizes the available energy and achieves maximum data through-put in each operating cycle. (Abstract shortened by UMI.)...