D
Dakai Zhu
Researcher at University of Texas at San Antonio
Publications - 106
Citations - 4075
Dakai Zhu is an academic researcher from University of Texas at San Antonio. The author has contributed to research in topics: Energy consumption & Scheduling (computing). The author has an hindex of 32, co-authored 102 publications receiving 3518 citations. Previous affiliations of Dakai Zhu include University of Pittsburgh.
Papers
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Journal ArticleDOI
Scheduling with dynamic voltage/speed adjustment using slack reclamation in multiprocessor real-time systems
TL;DR: This paper proposes two novel power-aware scheduling algorithms for task sets with and without precedence constraints executing on multiprocessor systems and proposes a new scheme of slack reservation to incorporate voltage/speed adjustment overhead in the scheduling algorithms.
Proceedings ArticleDOI
The effects of energy management on reliability in real-time embedded systems
TL;DR: In this article, the authors investigated the effects of frequency and voltage scaling on the fault rate and proposed two fault rate models based on previously published data and analyzed the effect of energy management on reliability.
Proceedings ArticleDOI
Energy aware scheduling for distributed real-time systems
TL;DR: To consider the run-time behavior of tasks, an on-line dynamic power management technique is proposed to further explore the idle periods of processors and it is found that this static technique can save an average of 10% more energy than the simple static power management.
Journal ArticleDOI
Reliability-Aware Energy Management for Periodic Real-Time Tasks
Hakan Aydin,Dakai Zhu +1 more
TL;DR: This work investigates static and dynamic reliability-aware energy management schemes to minimize energy consumption for periodic real-time systems while preserving system reliability and presents two integrated approaches to reclaim both static andynamic slack at runtime.
Proceedings ArticleDOI
Scheduling with dynamic voltage/speed adjustment using slack reclamation in multi-processor real-time systems
TL;DR: This paper proposes two novel scheduling algorithms for task sets with and without precedence constraints that reclaim the time unused by a task to reduce the execution speed of future tasks, and thus reduce the total energy consumption of the system.