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State machine diagram for RT – Scheduling.
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Energy efficiency is an important property of mobile and pervasive computing devices. Dynamic voltage scaling (DVS) is an energy saving technique, achieve this property by reducing energy dissipation of the core by lowering the supply voltage and operating frequency. In this paper a simulation environment for testing of different DVS algorithms und...
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Energy consumption has become an important aspect while designing a portable embedded system. Dynamic voltage scaling (DVS) is an energy saving technique, reducing energy dissipation of the core by lowering the supply voltage and operating frequency, so that battery life of portable devices can be extended. In this paper it is discussed about a sim...
While energy consumption and Quality of Service (QoS) are primary concerns for the design of embedded systems, reliability requirement has become increasingly important in the development of today’s pervasive computing systems. In this paper, we present a reliability-aware energy management (RAEM) scheme for reducing the energy consumption for (m,...
Citations
Limited battery power is a typical constraint in stand-alone embedded systems. One way to extend the battery lifetime is by reducing CPU power consumption. Because of the quadratic relationship between power consumption in CMOS circuits and CPU voltage, power reduction can be obtained by scaling down supply voltage, or dynamic voltage scaling. However, reducing supply voltage slows down CPU speed since supply voltage has a proportional relationship with CPU frequency. On the other hand, in any real-time embedded environment (especially hard real-time), timing constraints are critical. In this paper, we focus on dynamic energy reduction of tasks scheduled by rate monotonic (RM) algorithm in a hard real-time embedded environment. The RM algorithm preemptively schedules any set of periodic tasks by assigning higher priorities to frequent tasks. For any periodic task set that satisfies the CPU utilization bound, we determine the provably optimal scaling of the worst-case execution time of each task that consumes minimum dynamic energy while satisfying the utilization bound. As RM algorithm is widely used, we expect this work can lead to better energy reduction management and expectations.
The DVS(Dynamic Voltage Scaling) technique is the method to reduce the dynamic energy consumption. Using slack times, it extends the execution time of big load operations by changing frequency and voltage of variable voltage processors. Many researches have been going on to control the energy consumption of the processors and the data transmission among processors by controlling the bandwidth to reduce the energy consumption of the entire system. Since operations in multiprocessor systems have the data dependency between processors, however, the DVS techniques devised for single processors are not suitable to improve the energy efficiency of multiprocessor systems. We propose a new scheduling algorithm based on DVS for increasing energy efficiency of multiprocessor systems. The proposed DVS-based scheduling algorithm can improve the energy efficiency of entire systems because it controls frequency and voltages while considering the data dependency among processors.
