Performance Power Consumption Research Articles

Noise analysis and optimization of VCII-based SiPM interface circuit

Recently, second generation voltage conveyor (VCII)-based transimpedance amplifiers (TIAs) have begun to find their way in different applications, among which, silicon photomultipliers (SiPMs) interfacing circuitry. There are many advantages which make VCII-based TIAs attractive over conventional circuits: the intrinsic low impedance at VCII current input Y port is very helpful to mitigate the effect of high value sensor capacitance and provides fast response time; the achieved bandwidth is high and due to current mode operation; the circuits enjoy the low-voltage low-power features. As signal-to-noise ratio is a crucial parameter in SiPMs interface circuit applications, here we consider the noise specifications and optimization of VCII-based SiPM interface circuits. The noise model of VCII is introduced and equivalent noise of a VCII-based interface circuit is derived. Methods to optimize trade-offs existing between key parameters including power consumption, gain and noise performance are discussed. Simulation results are also provided showing a considerable reduction of two orders of magnitude in most of the noise performances when compared to the previous work while preserving other performance parameters.

C3S–QVCO: A low phase noise low power super–harmonic coupling QVCO with cross–connected common–source nodes

In this paper, a novel passive super–harmonic coupling QVCO is presented. The coupling is achieved by Cross–Connecting the top and bottom Common–Source nodes in the complementary (current reuse) LC Cross–Coupled oscillator topology, and therefore, the circuit is named as C3S–QVCO. Unlike the transformer coupling QVCO (TC–QVCO), as the typical super–harmonic coupling technique, the die area is not increased. Also, in the proposed QVCO, neither additional power consumption nor additional noise generator component is required, for quadrature operation. Therefore, the proposed QVCO has a good power consumption performance. The proposed method is evaluated theoretically and analytically, and it is proved that the proposed method is capable of generating multi–phase outputs. The proposed QVCO is designed in a 0.18 ​μm RF–CMOS technology with a power supply of 1.8 ​V, the current consumption of 6.25 ​mA, and the tuning range of 3.75–3.95 ​GHz (5.3%). Post layout simulation result shows −129 ​dBc/Hz, and 190 ​dB phase noise and FOM for the proposed QVCO at 1 ​MHz offset from the 3.75 ​GHz frequency. The proposed QVCO presents 6 ​dB phase noise improvement compared to parallel (P)–QVCO and also demonstrates similar phase noise performance to that of the TC–QVCO, with the same power consumption. Maximum phase/amplitude errors of the proposed QVCO for a 1% mismatch in the oscillator’s tank capacitors are 0.72°/2 ​mV, in the whole tuning range. Those are 0.77°/7.3 ​mV for the P–QVCO and 1.3°/2.3 ​mV for the TC–QVCO.

Features of ventilation at the enterprises of metallurgy and mechanical engineering

The processes of foundry of machine-building enterprises are accompanied by the release of excess heat and a large number of hazards. Reducing the harmful impact of enterprises on the environment should be ensured by a complex of technological and construction measures, as well as the effective operation of ventilation systems. When designing ventilation systems, it is necessary to solve an optimization problem that takes into account their energy and environmental reliability, and economic efficiency. As a result of the analysis of the reliability of ventilation systems, their energy efficiency, heat consumption for the needs of heating and ventilation of a number of metallurgical industries, in order to reduce operational energy costs, it is recommended to solve a set of problems that include increasing the level of use of secondary energy resources. The authors propose a cyclone-heat exchanger, where cleaning of dust and gas flow and its heat recovery are combined in one apparatus. Design and construction of energy-efficient ventilation systems with high technological reliability will reduce operating power consumption from 30 to 75%.

Wake symmetry impacts the performance of tandem hydrofoils during in-phase and out-of-phase oscillations differently.

The hydrodynamics of two oscillating foils in side-by-side configuration is numerically investigated for in-phase and out-of-phase pitching at Reynolds number of 4000 and Strouhal numbers of St=0.25-0.5. The effects of phase difference (in-phase and out-of-phase) and Strouhal number on symmetric attributes of the wake and unsteady propulsive performance of the foils are studied in detail. At lower Strouhal numbers, there is a quasisteady performance in both thrust generation and power consumption, which coincides with persistence of the wake symmetry. As Strouhal number increases, however, in-phase and out-of-phase pitching display unsteady cycle-averaged behavior with very different wake characteristics. The asymmetric wake of in-phase pitching foils at high Strouhal numbers transitions to a quasisymmetric wake, when an extensive interaction between the two vortex streets is observed in the wake. This coincides with an improvement on the propulsive performance of the foils. In contrast, the symmetric wake of the out-of-phase pitching foils at a high Strouhal number transitions to an asymmetric wake. The adverse effect of this transition is only observed on the propulsive performance of one foil while the other exploits the wake towards a better performance. The collective performance of the the out-of-phase pitching system, however, remains unchanged. There is also a strong correlation between the wake symmetric characteristics and total nonzero side-force production.

A Combined Filter for Synchronous Detection in Underwater Acoustic Mobile Communication System

A scale-stretching combined filter is proposed for underwater acoustic mobile communication receivers. The combined filter consists of the sum of signals with different time stretching and shifting. Based on the matched filtering theory, Doppler stretching scales, time shift, and the order of each component of the combined filter are derived. The method proposed in this paper improves the matching degree of the filter with wideband Doppler echo signals with different moving speeds. Simulation results show that the combined filter proposed in this paper can improve the detection probability and synchronization time estimation accuracy of wideband Doppler echo. In addition, the combined filter proposed in this paper has the same calculation amount as the matched filter. This feature makes this filter suitable for the synchronous detection of underwater acoustic mobile communication with real-time operation and low power consumption requirements.

Low-power self-oscillating fluxgate current sensor based on Mn-Zn ferrite cores

A low-power open-loop self-oscillating fluxgate current sensor based on Mn-Zn soft ferrites is proposed in the paper. Differential realization of compensation amplifier, in class-D full-bridge configuration, provides full theoretical reduction of power consumption, which is impossible in the case of standard half-bridge realization. Together with data provided from the ferrite manufacturers, offered set of simple equations can qualitatively estimate quiescent and operating power consumption, and help in avoidance of design solutions that lead to unnecessary power losses. If a commercial or custom transformer core, made of conventional industrial Mn-Zn ferrite materials is used, all important parameters for sensor design, and follow-on exploitation, can be predicted in advance. Experimental examinations show that power consumption can be reduced to the level of open-loop Hall-effect based sensor, while many comparable advantages of flux-gate technology are maintained. We design sensor and tuned circuit parameters to measure currents in the range of [–20 A, 20 A] with an overcurrent capability of 50%. In temperature range of [–20 °C, 50 °C], maximum relative linearity error of 0.25% and offset drift of 0.05% is achieved.

Design and Implementation of CNTFET-Based Reversible Combinational Digital Circuits Using the GDI Technique for Ultra-low Power Applications

It is obvious that the design of low power digital circuits is very important. Hence, reversible logic can be used as the great method for reducing power consumption. In this paper, we attempt to present various CNTFET-based reversible combinational circuits such as multiplexers and decoders by simultaneous use of the reversible Fredkin gate and Gate Diffusion Input (GDI) technique. At first, we illustrate the block diagram of multiplexers and decoders according to the definition of reversible gates. Then, we introduce the design approach of CNTFET-based circuits by using the GDI technique. All structures are simulated using Synopsys HSPICE with standard 32 nm CNTFET technology in various conditions including temperature 27 °C, simulation time from zero to 100 ns, and other parameters are the variable. In this work, we investigate the variation effect of supply voltage, temperature, number of nanotubes, and chiral vector in performance evaluation of the mentioned circuits. In addition, the ECPOT analysis is reported. According to the results, the proposed CNTFET-based reversible multiplexers achieve a significant saving in average power consumption (approximately 99.99% for 2:1 multiplexer, 99.95% for 4:1 multiplexer, 99.96% for 8:1 multiplexer compared with the best previous work) and the average power consumption for 16:1 multiplexer is 25.47 nw. The proposed CNTFET-based reversible decoders have high performance in the average power consumption (approximately 99.99% for 2:4 decoder, 99.99% for 3:8 decoder, and 99.22% for 4:16 decoder compared with the best previous work). Moreover, applying these suggested circuits significantly improves the speed, PDP, and EDP of complex arithmetic structures.

Low-voltage complementary inverters using solution-processed, high-mobility organic single-crystal transistors fabricated by polymer-blend printing

Organic field-effect transistors (OFETs) have attracted great attention as key elements in Internet-of-Thing (IoT) devices due to their advantages of low cost and mass producibility made possible by printing technology. Such devices require organic semiconductors (OSCs) that intrinsically possess high carrier mobility and air stability. In addition, the demand for low-voltage operation and low power consumption has been increasing because the potential power sources for actual devices are implementable energy harvesters that supply low power and low voltages. Based on recently developed high-performance single-crystal p-type and n-type OSCs, this work demonstrated air-stable, high-mobility OFETs with low-voltage operation by using an insulating polymer-blend printing method. By comparing two acrylic polymers poly(methyl methacrylate) and poly(adamantyl methacrylate) (PADMA), having remarkably different thermal properties, we found that PADMA showing a high glass transition temperature >200 °C was suitable for device fabrication, enhancing the flexibility of OSC materials. Also, PADMA spontaneously produced good charge-transport interfaces with the OSC single crystals, leading to high carrier mobilities of 6.6 and 2.2 cm2 V−1 s−1 in p-channel and n-channel OFETs at ≤1.5 V, respectively. The current electron mobility was the highest among low voltage-operation OFETs reported so far. These high-mobility OFETs were integrated into a complementary inverter, for which a low static power consumption of 6.6 pW was confirmed. Therefore, this study reports an advantage of polymer-blend printing for OFETs with enhanced processability and performance suitable for IoT applications.

A study on the energy and exergy of Ohmic heating (OH) process of sour orange juice using an artificial neural network (ANN) and response surface methodology (RSM).

The nonmodern statistical methods are often unusable for modeling complex and nonlinear calculations. Therefore, the present research modeled and investigated the energy and exergy of the ohmic heating process using an artificial neural network and response surface method (RSM). The radial basis function (RBF) and the multi‐layer perceptron (MLP) networks were used for modeling using sigmoid, linear, and hyperbolic tangent activation functions. The input consisted of voltage gradient; weight loss percentage, duration ohmic, Input flow, Power consumption, electrical conductivity and system performance coefficient and the output included the energy efficiency, exergy efficiency, exergy loss, and improvement potential. The response surface method was also used to predict the data. According to the result, the best prediction amount for energy and exergy efficiencies, exergy loss and improvement potential were in RBF network by sigmoid activation function and after this network, RSM had the best amount for energy efficiency, Also for exergy efficiencies, exergy loss and improvement potential obtained acceptable results in MLP network by a linear activation function. The worst amount was at MLP network by tangent hyperbolic. In general, the neural network can have more ability than the response surface method.

Performance evaluation of wireless sensor networks using LEACH protocol

<span>Recent days witnessed considerable developments in the field of wireless sensor networks (WSNs). The applications of these networks can be seen in the simple consumer electronic devices as well as in the advanced space technology. The communication protocols are of prior importance and interest; the low-energy adaptive clustering hierarchy (LEACH) protocol is used to enhance the performance of power consumption for the WSNs nodes. The efficiency of a wireless network can be affected by different factors, such as the size of the WSN and the initial energy of the sensor node. This can inspire the researchers to develop the optimum structure of the WSNs to get its desired functionality. In this paper, the performance of the low-energy adaptive clustering hierarchy (LEACH) protocol is investigated using MATLAB to study the effect of the initial energy of the sensor node and the WSN size on the number of the running nodes. It is found that increasing the initial energy of a sensor node increases the life time of the node and hence the number of the running nodes. It has been also approved that the WSN size has an inverse proportion with the number of running sensor nodes during the use of LEACH protocol.</span>

Air-Conditioner Group Power Control Optimization for PV integrated Micro-grid Peak-shaving

<p style='text-indent:20px;'>Heating, Ventilation, and Air-Condition (HVAC) systems are considered to be one of the essential applications for modern human life comfort. Due to global warming and population growth, the demand for such HVAC applications will continue to increase, especially in arid areas countries like the Arabian Gulf region. HVAC systems' energy consumption is very high and accounts for up to 70% of the total load consumption in some rapidly growing GCC countries such as Qatar. Additionally, the local extremely hot weather conditions usually lead to typical power demand peak issues that require adequate mitigation measures to ensure grid stability. In this paper, a novel control scheme for a combined group of Air-Conditioners is proposed as a peak-shaving strategy to address high power demand issues for Photo-Voltaic(PV)-integrated micro-grid applications. Using the local daily ambient temperature as input, the AC group control optimization is formulated as a Mixed-Integer Quadratic Programming (MIQP) problem. Under an acceptable range of indoor temperatures, the units in the same AC group are coordinately controlled to generate desired power consumption performance that is capable of shaving load peaks for both power consumption and PV generation. Finally, various simulations are performed that demonstrate the effectiveness of the proposed control strategy.</p>

MODELING OF HYBRID MOS FOR THE IMPLEMENTATION OF SWITCHED CAPACITOR FILTER USING SINGLE ELECTRON TRANSISTOR

In digital integrated circuit architectures, transistors serve as circuit switches to charge and discharge capacitors to the required logic voltage levels. A transistor is a three terminal semiconductor device used to amplify and switch electronic signals and electrical power. It has been observed that the Scaling down of electronic device sizes has been the fundamental strategy for improving the performance of ultra-large-scale integrated circuits (ULSIs). Metaloxide-semiconductor field-effect transistors (MOSFETs) have been the most prevalent electron devices for ULSI applications. A better device will be formed with the help of new technology, with high operating speed low and power consumption, which can be the future of electronics industry. A methodology for the electric simulation of MOS/SET hybrid circuits will be developed. As a result of this, a functional model for the single-electron transistor will obtain and Implement Switched Capacitor Filter with the help of designed hybrid MOS. The SET model can be easily coded in any hardware description language.

A Deep Recurrent Neural Network for Non-Intrusive Load Monitoring Based on Multi-Feature Input Space and Post-Processing

Non-intrusive load monitoring (NILM) is a process of estimating operational states and power consumption of individual appliances, which if implemented in real-time, can provide actionable feedback in terms of energy usage and personalized recommendations to consumers. Intelligent disaggregation algorithms such as deep neural networks can fulfill this objective if they possess high estimation accuracy and lowest generalization error. In order to achieve these two goals, this paper presents a disaggregation algorithm based on a deep recurrent neural network using multi-feature input space and post-processing. First, the mutual information method was used to select electrical parameters that had the most influence on the power consumption of each target appliance. Second, selected steady-state parameters based multi-feature input space (MFS) was used to train the 4-layered bidirectional long short-term memory (LSTM) model for each target appliance. Finally, a post-processing technique was used at the disaggregation stage to eliminate irrelevant predicted sequences, enhancing the classification and estimation accuracy of the algorithm. A comprehensive evaluation was conducted on 1-Hz sampled UKDALE and ECO datasets in a noised scenario with seen and unseen test cases. Performance evaluation showed that the MFS-LSTM algorithm is computationally efficient, scalable, and possesses better estimation accuracy in a noised scenario, and generalized to unseen loads as compared to benchmark algorithms. Presented results proved that the proposed algorithm fulfills practical application requirements and can be deployed in real-time.

Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design

The development of the nanoelectronics semiconductor devices leads to the shrinking of transistors channel into nanometer dimension. However, there are obstacles that appear with downscaling of the transistors primarily various short-channel effects. Graphene nanoribbon field-effect transistor (GNRFET) is an emerging technology that can potentially solve the issues of the conventional planar MOSFET imposed by quantum mechanical (QM) effects. GNRFET can also be used as static random-access memory (SRAM) circuit design due to its remarkable electronic properties. For high-speed operation, SRAM cells are more reliable and faster to be effectively utilized as memory cache. The transistor sizing constraint affects conventional 6T SRAM in a trade-off in access and write stability. This paper investigates on the stability performance in retention, access, and write mode of 15 nm GNRFET-based 6T and 8T SRAM cells with that of 16 nm FinFET and 16 nm MOSFET. The design and simulation of the SRAM model are simulated in synopsys HSPICE. GNRFET, FinFET, and MOSFET 8T SRAM cells give better performance in static noise margin (SNM) and power consumption than 6T SRAM cells. The simulation results reveal that the GNRFET, FinFET, and MOSFET-based 8T SRAM cells improved access static noise margin considerably by 58.1%, 28%, and 20.5%, respectively, as well as average power consumption significantly by 97.27%, 99.05%, and 83.3%, respectively, to the GNRFET, FinFET, and MOSFET-based 6T SRAM design.

Field performance of an electric–hydraulic control system for vibrating subsoiler with flexible tines

Vibrating subsoilers with flexible tines exhibit effective obstacle avoidance and soil loosening. However, undesired depths, much less than target value, are observed for subsoilers using springs as excitation elements. Therefore, we studied electric–hydraulic control technology to improve the adaptability of the vibrating subsoiler to various soil conditions by adjusting the working pressure of the excitation element. Based on a previous study of the electric–hydraulic control system that was designed for single flexible tine (Wang et al., 2018), we improved it to allow it to be applied to various rows of subsoilers in this study. Additionally, the effect of the improved electric–hydraulic control system on the subsoil quality (tillage depth, inter-row and in-row variations of tillage depth, soil bulk density, and cone index) and tool operation (draft force and power consumption) in field conditions was investigated and compared with the classical spring system. Field tests showed that the improved electric–hydraulic control system exhibited more qualified operation results compared with the classical spring system. The excitation element for each flexible tine were adjusted independently, thereby reducing the variation of the inter-row and in-row tillage depth. The variation coefficients of the electric–hydraulic system decreased by 17.59% and 34.1% when the operating speed increased from 4.2 km/h to 5.3 and 6.2 km/h, respectively, relative to spring system. Moreover, the electric–hydraulic control system yielded better soil loosening. The soil bulk density decreased by 4.55%, 3.87%, 4.59, and 4.81% at depths of 25, 30, 35, and 40 cm, respectively. However, due to the power requirement of the tractor due to the hydraulic output, the total power of the electric–hydraulic control system slightly increased by within 6.5% compared with the rigid system. Therefore, further research is needed to achieve power saving through hydraulic system optimization.

AN IMPROVED PRE-FORECASTING ANALYSIS OF ELECTRICAL LOADS OF PUMPING STATION

Relevance of research. In order to reduce energy losses, an accurate and timely forecast of the amount of consumed electricity is necessary. Accurate forecasting of electrical loads of industrial enterprises and their divisions (productions, workshops, departments etc.) allows planning of normal operating conditions, concluding contracts for the electricity supply with the electricity supply company under more favorable conditions, and improving the electricity quality, which ultimately affects the final cost of the products produced by an enterprise. So far, more than 150 forecasting methods of electrical loads have been developed. Usually, the most convenient one is selected based on the forecaster experience by creating and analyzing several forecasting models in order to identify the best. Therefore, in order to simplify the forecasting procedure, it is necessary to develop the methodology for forecasting analysis. This methodology should enable canceling forecasting algorithms that will create lower quality forecasts. The main objective is to develop the methodology for making a forecasting analysis of power consumption on the example of a pumping station of an enterprise with a continuous cycle of work to increase the efficiency of energy consumption and implementation of energy-saving measures. Objects of research: the process of forecasting electrical loads of a pumping station of the enterprise with a continuous cycle of work. Methods of research: fundamental principles of the theory of electrical engineering, statistical methods for power consumption forecasting, the method for detecting the trend of radio signals, and fractal analysis of time series. Research results. The methodology for forecasting analysis of power consumption, which makes it possible to apply the most appropriate methods to forecast the operational power consumption, is developed. For the first time, the radio signal trend detection method is applied to identify the trend of electrical loads. The variation ranges of the fractal parameters of time series of electrical loads are established depending on the variation coefficient of the time series for different periods of time. The Brown method of exponential smoothing that is used to forecast the electrical loads, in the case of identifying the smoothing constant α is in the beyond set ( ), is further improved. The regularity of changes in the fractal parameters of time series of power consumption of a pumping station with an increase in the time series duration and their field of application are explained.

AN IMPROVED PRE-FORECASTING ANALYSIS OF ELECTRICAL LOADS OF PUMPING STATION

Relevance of research. In order to reduce energy losses, an accurate and timely forecast of the amount of consumed electricity is necessary. Accurate forecasting of electrical loads of industrial enterprises and their divisions (productions, workshops, departments etc.) allows planning of normal operating conditions, concluding contracts for the electricity supply with the electricity supply company under more favorable conditions, and improving the electricity quality, which ultimately affects the final cost of the products produced by an enterprise. So far, more than 150 forecasting methods of electrical loads have been developed. Usually, the most convenient one is selected based on the forecaster experience by creating and analyzing several forecasting models in order to identify the best. Therefore, in order to simplify the forecasting procedure, it is necessary to develop the methodology for forecasting analysis. This methodology should enable canceling forecasting algorithms that will create lower quality forecasts. The main objective is to develop the methodology for making a forecasting analysis of power consumption on the example of a pumping station of an enterprise with a continuous cycle of work to increase the efficiency of energy consumption and implementation of energy-saving measures. Objects of research: the process of forecasting electrical loads of a pumping station of the enterprise with a continuous cycle of work. Methods of research: fundamental principles of the theory of electrical engineering, statistical methods for power consumption forecasting, the method for detecting the trend of radio signals, and fractal analysis of time series. Research results. The methodology for forecasting analysis of power consumption, which makes it possible to apply the most appropriate methods to forecast the operational power consumption, is developed. For the first time, the radio signal trend detection method is applied to identify the trend of electrical loads. The variation ranges of the fractal parameters of time series of electrical loads are established depending on the variation coefficient of the time series for different periods of time. The Brown method of exponential smoothing that is used to forecast the electrical loads, in the case of identifying the smoothing constant α is in the beyond set ( ), is further improved. The regularity of changes in the fractal parameters of time series of power consumption of a pumping station with an increase in the time series duration and their field of application are explained.

Speed enhancement techniques for Clock-Delayed Dual Keeper Domino logic style

ABSTRACT Domino circuit topology for high-speed operation, robustness and lower power consumption is quintessential in design of digital systems. In this paper, various high speed and robust mechanisms are proposed to enhance the speed of Clock-Delayed Dual Keeper Domino (CDDK) circuit. Delayed enabling of keeper circuit in CDDK domino circuit reduces contention between keeper circuit and Pull-Down network (PDN). The speed of transition at the dynamic node of the CDDK domino circuit is enhanced through imposing techniques namely (i) controlled clock delay time in enabling the keeper transistor, (ii) keeper control signal voltage swing variation, (iii) sizing of keeper transistors and (iv) deploying an additional conditional discharge path. The robustness of CDDK circuit is increased by upsizing the keeper transistor without degrading the speed by stack arrangement of dual keeper transistors. The simulation of enhancement techniques has been performed using Cadence® Virtuoso ADEL and ADEXL environments employing UMC 90nm technology library. The simulation results of wide fan-in 64-input OR gate demonstrate that CDDK technique with additional discharge path offer 38% increase in speed and CDDK technique with keeper transistor upsizing offers 52% increase in noise gain margin without speed degradation while comparing with the conventional domino logic circuit.

Edge-Aided Computing and Transmission Scheduling for LTE-U-Enabled IoT

To facilitate the deployment of private industrial Internet-of-Things (IoT), applying long-term-evolution (LTE) over unlicensed spectrum (LTE-U) is a promising technology, which can deal with the licensed spectrum scarcity problem and the stringent quality-of-service (QoS) requirement via centralized control. In this paper, we investigate the computing offloading problem for LTE-U-enabled IoT, where computing tasks on an IoT device are either executed locally or offloaded to the edge server on an LTE-U base station. Considering a constrained edge computing cost (e.g., operation power consumption) for offloaded tasks, the task scheduling problem is formulated as a constrained Markov decision process (CMDP) to maximize the long-term average reward, which integrates both task completion profit and task completion delay. In order to address the uncertainty of task arrivals and channel availability, a constrained deep Q-learning-based task scheduling algorithm with provable convergence is proposed, where an adaptive reward function can appropriately bound the average edge computing cost. Extensive simulation results show that the proposed scheme considerably enhances the system performance.

Optimal Power Management System in Embedded Devices by using Novel Scheduling Algorithm

Recently, Android is being integrated and applied to various embedded systems because of good characteristics like open source, a wide connective range, multitasking, and secure communications. Most of the modern embedded designers have been focused on system performance while reducing operating power consumption. However, increasing the performance level inevitably increases power consumption. In this article, an optimal power management (OPM) system is proposed for embedded systems using a novel scheduling algorithm. It can control the operating power consumption of open source platforms (Raspberry-PI, Parallella, and Arduino) supported hardware devices (ZynqBerry, ZynqParallela, and ArduZynq). The proposed OPM system uses the scheduling algorithm based on the functionality of optimization and their tasks. Moreover, the proposed OPM system provides the low or high frequency to the devices upon receiving the low frequency and high frequency request from the devices. The simulation result is calculated in terms power consumption, maximum operating frequency and hardware utilization.