In the upcoming Internet of Things era, reducing energy consumption of embedded processors is highly desired. Minimum Energy Point Tracking (MEPT) is one of the most efficient methods to reduce both dynamic and static energy consumption of a processor. Previous works proposed a variety of MEPT methods over the past years. However, none of them incorporate their algorithms with practical real-time operating systems, although edge computing applications often require low energy task execution with guaranteeing real-time properties. The difficulty comes from the time complexity for identifying an MEP and changing voltages, which often prevents real-time task scheduling. The conventional Dynamic Voltage and Frequency Scaling (DVFS) only scales the supply voltage. On the other hand, MEPT needs to adjust the body bias voltage in addition. This additional tuning knob makes MEPT much more complicated. This paper proposes an approximate MEPT algorithm, which reduces the complexity of identifying an MEP down to that of DVFS. The key idea is to linearly approximate the relationship between the processor frequency, supply voltage, and body bias voltage. Thanks to the approximation, optimal voltages for a specified clock frequency can be derived immediately. We also propose a task scheduling algorithm, which adjusts processor performance to the workload and then provides a soft real-time capability to the system. The operating system stochastically adjusts the average response time of the processor to be equal to a specified deadline. MEPT will be performed as a general task, and its overhead is considered in the calculation of the frequency. The experiments using a fabricated test chip and on-chip sensors show that the proposed algorithm is a maximum of 16 times more energy-efficient than DVFS. Also, the energy loss induced by the approximation is only 3% at most, and the algorithm does not sacrifice the fundamental real-time properties.

A new approach to build up a real-time multiprocessing system that is configuration flexible for evaluating space-time (ST) equalizers is described. The core of the system consists of fully programmable devices such as digital signal processors (DSPs), field-programmable gate arrays (FPGAs), and reduced instruction set computers (RISCs) with a real-time operating system (RTOS). The RTOS facilitates flexibility in the multi-processor configuration for the system conforming with ST processing algorithms. Timing jitter synchronization caused by use of the RTOS-embedded system is shown, and an adjustable frame format for a transmission system is described as a measure to avoid the jitter problem. Bit error rate (BER) performances measured in uncorrelated frequency-selective fading channels show that an ST equalizer provides a significantly lower BER than an array processor does.