Power Consumption Cost Research Articles

Multi-Layer Fog-Cloud Architecture for Optimizing the Placement of IoT Applications in Smart Cities

In the smart city paradigm, the deployment of Internet of Things (IoT) services and solutions requires extensive communication and computing resources to place and process IoT applications in real time, which consumes a lot of energy and increases operational costs. Usually, IoT applications are placed in the cloud to provide high-quality services and scalable resources. However, the existing cloud-based approach should consider the above constraints to efficiently place and process IoT applications. In this paper, an efficient optimization approach for placing IoT applications in a multi-layer fog-cloud environment is proposed using a mathematical model (Mixed-Integer Linear Programming (MILP)). This approach takes into account IoT application requirements, available resource capacities, and geographical locations of servers, which would help optimize IoT application placement decisions, considering multiple objectives such as data transmission, power consumption, and cost. Simulation experiments were conducted with various IoT applications (e.g., augmented reality, infotainment, healthcare, and compute-intensive) to simulate realistic scenarios. The results showed that the proposed approach outperformed the existing cloud-based approach in terms of reducing data transmission by 64% and the associated processing and networking power consumption costs by up to 78%. Finally, a heuristic approach was developed to validate and imitate the presented approach. It showed comparable outcomes to the proposed model, with the gap between them reach to a maximum of 5.4% of the total power consumption.

An external-compression air separation unit with energy storage and its thermodynamic and economic analysis

Long-term supply demand balance in a power grid may be maintained by electric energy storage. Liquid air energy storage (LAES) can effectively store off-peak electric energy, and it is extremely helpful for electric decarburisation; however, it also has problems of high cost, long investment payback period and low efficiency because of its very low liquefaction temperature. Air liquefaction is the basic process of air separation, and the total electricity consumption of air separation units in China accounts for about 5.24 % of its national electricity consumption. Moreover, there remains a surplus of production capacity in air separation. This paper proposes an external-compression air separation process, with liquid air energy storage function. It can effectively reduce the power consumption cost of air separation unit while realizing peak load shifting. The system consists of three subsystems, namely, air separation; air liquefaction and storage; and power generation and air recovery. Research on equipment power consumption, economic benefits, and power grid peak shaving effect, indicates that the round-trip efficiency is 54.52 %, the electricity cost saving rate is 5.13 % based on Shanghai's peak-valley industrial electricity price, and the minimum dynamic payback period is 5.5 years. The large-scale application of this process can reduce the average peak-to-valley difference rate in China by 4.95 %. The transfer of peak regulating load to the base load of the power grid can save 5.2 × 106 toe, which will result in a 2.1 × 107 ton reduction in carbon dioxide emissions annually.

Ferroelectric Devices for Content-Addressable Memory.

In-memory computing is an attractive solution for reducing power consumption and memory access latency cost by performing certain computations directly in memory without reading operands and sending them to arithmetic logic units. Content-addressable memory (CAM) is an ideal way to smooth out the distinction between storage and processing, since each memory cell is a processing unit. CAM compares the search input with a table of stored data and returns the matched data address. The issues of constructing binary and ternary content-addressable memory (CAM and TCAM) based on ferroelectric devices are considered. A review of ferroelectric materials and devices is carried out, including on ferroelectric transistors (FeFET), ferroelectric tunnel diodes (FTJ), and ferroelectric memristors.

Energy cost optimization of globally distributed Internet Data Centers by copula-based multidimensional correlation modeling

The high operating costs of Internet Data Centers (IDC) are a major challenge for their owners worldwide. Therefore, more attention has recently been paid to the energy and cost management of IDCs. This paper investigates the optimal operational strategy for minimizing the electricity costs of a group of globally distributed IDCs in different locations under various day-ahead electricity markets, and each is equipped with a high-performance energy storage system. For this goal, optimal workload dispatching and optimal energy management of the storage units of all IDCs are simultaneously perused by the proposed problem. The system is modeled regarding power balancing constraints, battery costs, and quality of service (QoS). For more practical results, a penalty function is also considered when QoS constraints are not perfectly met, and the impact of the batteries’ depth of discharge on the cost of energy storage is also modeled. Moreover, the cross-correlations between the traffic of IDCs are also considered by the multidimensional copula function. The proposed energy cost optimization is linearized for increasing the accuracy of convergence. The results show that not only the power consumption pattern of the IDCs is significantly improved, but also the cost of power consumption is reduced by 34%. The results also prove the positive effect of battery discharge on workload dispatch and represent a compromise between battery costs and electricity cost savings.

A demand side controller of electrolytic aluminum industrial microgrids considering wind power fluctuations

Direct wind power purchase for large industrial users is a meaningful way to improve wind power consumption and decrease industrial production costs. Short-term wind power fluctuations may lead to large-scale wind power curtailment problems. To promote use of wind energy, a demand side control method is proposed based on output regulator theory for a grid-connected industrial microgrid with electrolytic aluminum loads to continuously track and respond to wind power fluctuations. The control model of the EALs and the dominant frequencies of the wind power fluctuation signals are analyzed and incorporated into the demand side control plant. The feedback control signals with active power deviations on the tie-line are used to design the demand side controller. Simulations are conducted for an actual industrial microgrid to validate the feasibility and effectiveness of the proposed method. The results demonstrate that the proposed controller based on output regulator theory is able to effectively track wind power fluctuations.

Single event upset reinforcement technology of DICE flip-flop based on layout design

D flip-flop is the basis of timing logic circuit, and SEMU phenomenon tends to be serious with the integrated circuit process size shrinking to nanometer scale. The anti-SEU ability based on DICE structure for D flip-flop cannot meet the requirements of aerospace engineering. Based on the SEU reinforcement technology of D flip-flop under nano-technology and the SEU mechanism of DICE structure, a layout-level anti-SEU flip-flop design method based on DICE circuit structure is proposed considering the circuit performance, area, power consumption and other resource costs. And then a D flip-flop with SEU resistance is designed by commercial 65 nm process, and the designed flip-flop area is 1.8 times that of commercial structure flip-flop. The function and and radiation simulation results indicate that the establishment time and transmission delay of the flip-flop are equivalent to those of the commercial one, and no SEU occurs under the Ge ion bombardment with the LET threshold of approximately 37 MeV·cm2/mg. The performance of the flip-flop circuit and the ability to resist single particle soft error are excellent. In the anti-radiation ASIC design, the area, wiring resources and timing overhead caused by the reinforcement of the D flip-flop circuit are greatly saved.

Investigation of optimum FSO communication link using different modulation techniques under fog conditions

The FSO communication system offers high data rate investigated over the last few decades because of extraordinary advantages like unlicensed frequency and bandwidth at low power consumption, simple design, hasty, and minimal installation cost, including no right of way. It is essential to investigate solutions against degrading factors like absorption and scattering caused by fog, dust, rain, smog, and uncertain temperature variation of environmental channels. In this work various modulation techniques (AM, CS-NRZ, CS-RZ, DB-NRZ, MDB-NRZ, MDB-RZ, RZ, NRZ) are simulated and used to mitigate the weather attenuation of the specific airfield of Lahore, Pakistan under fog conditions, to provide a reliable FSO communication link for high data rate up to 40 Gbps over a link distance from 1.2 to 1.8 km at transmitted power up to 34 dBm in congested region. The real-time visibility data was taken metrological department for the estimation of attenuation under fog conditions and simulated using Optisys software for further investigation. To choose an FSO communication link, analysis for data rate, link distance, SNR, BER and Q-factor are performed under fog conditions using eight different modulation techniques. An increase in signal channel loss has been observed under fog conditions and performance of the FSO communication system is degraded consequently. The 3 R’s (range, rate, and reliability) depend on each other if the link range is tarnished in a foggy condition that will also degrade the data rate and subsequently, reliability of the FSO system. It is observed that for maximum link distance, the performance parameters of AM modulation technique are prominent and more efficient, offering better Q-factor value at 6.08 dB, lower bit error rate at 7.03 × 10−10, and better SNR of 4.29 dB. The results also show that AM modulation technique offers better signal-to-noise power and has good SNR due to well-received signal power as compared to all other modulation techniques. This research will be helpful to design and implement an FSO communication system under foggy conditions in a metropolitan city to provide a high data communication link among different national institutions.

Hybrid Precoder Using Stiefel Manifold Optimization for Mm-Wave Massive MIMO System

Due to the increasing demand for fast data rates and large spectra, millimeter-wave technology plays a vital role in the advancement of 5G communication. The idea behind Mm-Wave communications is to take advantage of the huge and unexploited bandwidth to cope with future multigigabit-per-second mobile data rates, imaging, and multimedia applications. In Mm-Wave systems, digital precoding provides optimal performance at the cost of complexity and power consumption. Therefore, hybrid precoding, i.e., analog–digital precoding, has received significant consideration as a favorable alternative to digital precoding. The conventional methods related to hybrid precoding suffer from low spectral efficiency and large processing time due to nested loops and the number of iterations. A manifold optimization-based algorithm using the gradient method is proposed to increase the spectral efficiency to be near optimal and to speed up the processing speed. A comparison of performances is shown using the simulation outcomes of the proposed work and those of the existing techniques.

A Ship Exhaust Gas Monitoring Equipment based on NBIoT

Because of the severe problem of ship exhaust pollutant emission and the high cost, high power consumption of relevant ship exhaust monitoring schemes in the market, a ship exhaust monitoring equipment based on NBIoT (Narrow Band Internet of Things) is designed in this study. This equipment includes four parts: the power management unit, the minimum system unit, the communication circuit unit and the ship exhaust gas monitoring circuit unit. The overall process of the equipment is that the power management unit supplies power for the whole system; the minimum system unit starts the processing program and NBIoT communication program of ship exhaust gas monitoring; after receiving the power supply, the minimum system unit uploads the ship exhaust gas parameters measured by the ship exhaust gas monitoring circuit unit to the CVM(Cloud Virtual Machine) through the communication circuit unit. In this study, the ship exhaust monitoring equipment is installed at a fixed point in Gezhouba, and the coordinate position of the equipment is manually input to the cloud to conduct real-time monitoring of the exhaust emission of vessels passing through the lock. The results show that the equipment integrates ultra-low power consumption and low cost, is easy to set up, and can operate stably. It realizes real-time monitoring of SO2, CO2, NO2, and NO pollutants from ship exhaust.

Toward an Intelligent Campus: IoT Platform for Remote Monitoring and Control of Smart Buildings

With the growing need to obtain information about power consumption in buildings, it is necessary to investigate how to collect, store, and visualize such information using low-cost solutions. Currently, the available building management solutions are expensive and challenging to support small and medium-sized buildings. Unfortunately, not all buildings are intelligent, making it difficult to obtain such data from energy measurement devices and appliances or access such information. The internet of things (IoT) opens new opportunities to support real-time monitoring and control to achieve future smart buildings. This work proposes an IoT platform for remote monitoring and control of smart buildings, which consists of four-layer architecture: power layer, data acquisition layer, communication network layer, and application layer. The proposed platform allows data collection for energy consumption, data storage, and visualization. Various sensor nodes and measurement devices are considered to collect information on energy use from different building spaces. The proposed solution has been designed, implemented, and tested on a university campus considering three scenarios: an office, a classroom, and a laboratory. This work provides a guideline for future implementation of intelligent buildings using low-cost open-source solutions to enable building automation, minimize power consumption costs, and guarantee end-user comfort.

Multi-objective optimization model of micro-grid access to 5G base station under the background of China’s carbon peak shaving and carbon neutrality targets

Abstract: a large number of 5G base station are connected, which provides a new possibility for the future low-carbon development of power systems. By encouraging 5G base station to participate in demand response and incorporating it into the Microgrid, it can reduce the power consumption cost of 5G base stations and promote the efficient utilization of renewable energy. Based on the microgrid operation structure, 5G base station and multi-objective problem algorithm, a multi-objective optimization operation model of microgrid access to 5G base station is built. Considering the physical constraints of Microgrid, the objective is to minimize the operating cost and carbon emission. Through the joint dispatching of distributed clean energy generation, micro gas turbine, energy storage system and 5G base station in Microgrid, the comprehensive optimization of system economy and low-carbon benefits can be achieved. In this paper, a microgrid in Beijing is taken as the research object, and the Whale Optimization Algorithm algorithm is used to solve the multiobjective problem. The analysis results show that 5G base station can flexibly respond to microgrid scheduling, which helps microgrid to improve the consumption and utilization efficiency of renewable energy, thus bringing higher economic benefits and low-carbon benefits, and helping China to achieve the goal of carbon peak shaving and carbon neutrality at an early date.

Energy-conscious maintenance and production scheduling for single machine systems under time-of-use tariffs

In view of the joint optimization problem of preventive maintenance and production scheduling for modern production systems under time-of-use tariffs, a two-stage joint decision-making policy is proposed to achieve the peak-shifting reduction of production power. In the first stage, a dynamic preventive maintenance schedule is sequentially obtained based on the availability of machine. In the second stage, the production scheduling optimization of multi-workpiece processing is further carried out. The power consumption cost and the delay penalty cost under the time-of-use electricity tariff are considered, and the mixed integer programming model is established to achieve the balance of energy consumption and production delay. Numerical experiments have shown that by reasonably planning the idle time at the time of production batch conversion, the proposed model can effectively shift the on-peak power demand to off-peak, meet the stable electricity demand of enterprises, and improve the sustainable utilization level of power.

A 0.3-V, −75.8-dBm Temperature-Robust Differential Wake-Up Receiver for WSNs

This article presents a 0.3-V, −75.8-dBm differential wake-up receiver (WuRX) with temperature robustness for wireless sensor network (WSN) applications. In this work, an adaptive gate-biased pseudo-differential envelope detector (ED) with temperature compensation is proposed to achieve high conversion gain, wide range of tunability, and temperature robustness at the cost of low power consumption. To address the problem that the high supply voltage of the baseband amplifier (BB-AMP) limits the further reduction of the overall system supply voltage, a bulk-driven differential BB-AMP is also proposed, the characteristics of its ultralow supply voltage make the system supply voltage as low as 0.3 V. And the dual path offset calibration loop is proposed to eliminate all mismatches and offsets in the differential signal path, further ensuring the system robustness. This WuRX is implemented in a 65-nm LP CMOS process, operates at 434 MHz, consumes 6.96 nW from 0.3-V supply voltage, and achieves a sensitivity of −75.8 dBm at 250 bps. When the temperature changes from −10 °C to 50 °C, the sensitivity varies from −77.5 to −73.6 dBm.

Capacity Bounds for One-Bit MIMO Gaussian Channels With Analog Combining

The use of 1-bit analog-to-digital converters (ADCs) is seen as a promising approach to significantly reduce the power consumption and hardware cost of multiple-input multiple-output (MIMO) receivers. However, the nonlinear distortion due to 1-bit quantization fundamentally changes the optimal communication strategy and also imposes a capacity penalty to the system. In this paper, the capacity of a Gaussian MIMO channel in which the antenna outputs are processed by an analog linear combiner and then quantized by a set of zero threshold ADCs is studied. A new capacity upper bound for the zero threshold case is established that is tighter than the bounds available in the literature. In addition, we propose an achievability scheme which configures the analog combiner to create parallel Gaussian channels with phase quantization at the output. Under this class of analog combiners, an algorithm is presented that identifies the analog combiner and input distribution that maximize the achievable rate. Numerical results are provided showing that the rate of the achievability scheme is tight in the low signal-to-noise ratio (SNR) regime. Finally, a new 1-bit MIMO receiver architecture which employs analog temporal and spatial processing is proposed. The proposed receiver attains the capacity in the high SNR regime.

A Multi-Objective Fuzzy Optimization Model for Electricity Generation and Consumption Management in a Micro Smart Grid

This manuscript proposes an intelligent supply and demand management system in a complete network of electricity production and consumption. A micro smart grid (MSG), which includes a solar cell, a wind turbine, a diesel generator, and battery storage system capable of trading energy with the smart gride (SG), connected to smart buildings with different types of loads is modelled. Different types of intelligent fuzzy controllers for distributed management were proposed and optimized via the non-dominated sorting genetic algorithm-II (NSGAII), which is a multi-objective optimization method. Maximum user comfort, the amount of renewable energy employment, minimum total power consumption cost, total energy consumption at peak time, and MSG loss of power supply probability are the five objective functions of the optimization process. Various uncertainties of the real world have also been considered. The most crucial distinguishing feature of this proposed method is the design of controllers to manage the demand and supply of electricity without the need for daily optimization. Comparison experiments with other methods presented in the field of electricity supply and demand management are conducted to show the superiority of this method in terms of optimality of the results, low processing volume required to implement real controllers, and its resilience to changing conditions.

A Reliable Framework for Secure Communication and Health Assessment of Soldiers in the Battlefield

Wars against the enemy are mandatory for the integrity of a nation. With the passage of time, the nature of war is being changed, to some extent from a conventional war to the network-centric warfare. The rate of soldiers death has increased in modern combat operations. The lack of secure connectivity and the health (mental and physical) of soldiers are among a few major reasons for the increased mortality. Mental health or stress level produces permanent changes in the physiological systems of a soldier and long-term diseases such as asthma, diabetes, and hypertension are activated with chronic stress. Although modern communication technologies may provide huge support in the efficient conduction of combat’s activities but it is at the cost of huge power consumption. The proposed research presents a computationally efficient and low-power framework that not only ensures secure communication but also provides a robust command and control system to monitor the mental stress, injury, and death of soldiers. In the suggested framework, the Advanced Encryption Standard (AES) is used for communication that is highly suitable for power constraint devices. A wearable sensor system is suggested that can be embedded in a soldier’s uniform to assist in the recording of real-time stress, injury, and death of soldiers. The system contains a heart-rate monitor to record variations in heartbeats, an EDA sensor for skin conductance, and a respiration sensor for respiration variations along with a holster unit for storage and transmission of biomedical signals. Furthermore, it also provides a mechanism to prevent misuse of soldiers’ communication equipment by the enemy thus ensuring more security. The experimental analysis shows that the proposed mental stress computation module achieved 83.33% accuracy. Moreover, a score-based comparison is performed with the existing techniques and it is found that the proposed mechanism outperformed its counterparts with 37.5% improvements in the features-based analysis. The flexibility, security, efficiency, and reliability of the framework make it appropriate for modern warfare scenarios.

A Review of MEMS Vibrating Gyroscopes and Their Reliability Issues in Harsh Environments

Micro-electromechanical systems (MEMS) vibrating gyroscopes have gained a lot of attention over the last two decades because of their low power consumption, easy integration, and low fabrication cost. The usage of the gyroscope equipped with an inertial measurement unit has increased tremendously, with applications ranging from household devices to smart electronics to military equipment. However, reliability issues are still a concern when operating this inertial sensor in harsh environments, such as to control the movement and alignment of mini-satellites in space, tracking firefighters at an elevated temperature, and assisting aircraft navigation in gusty turbulent air. This review paper focuses on the key fundamentals of the MEMS vibrating gyroscopes, first discussing popular designs including the tuning fork, gimbal, vibrating ring, and multi-axis gyroscopes. It further investigates how bias stability, angle random walk, scale factor, and other performance parameters are affected in harsh environments and then discusses the reliability issues of the gyroscopes.

An Improved Sparrow Search Algorithm for Solving the Energy-Saving Flexible Job Shop Scheduling Problem

Due to emerging requirements and pressures related to environmental protection, manufacturing enterprises have expressed growing concern for adopting various energy-saving strategies. However, environmental criteria were usually not considered in traditional production scheduling problems. To overcome this deficiency, energy-saving scheduling has drawn more and more attention from academic scholars and industrial practitioners. In this paper, an energy-saving flexible job shop scheduling problem (EFJSP) is introduced in accordance with the criterion of optimizing power consumption and processing costs simultaneously. Since the classical FJSP is strongly NP-hard, an Improved Sparrow Search Algorithm (ISSA) is developed for efficiently solving the EFJSP. In the ISSA, a Hybrid Search (HS) method is used to produce an initial high-quality population; a Quantum Rotation Gate (QRG) and a Sine–Cosine Algorithm (SCA) are integrated to intensify the ability of the ISSA to coordinate exploration and exploitation; the adaptive adjustment strategy and Variable Neighborhood Search (VNS) are applied to strengthen diversification of the ISSA to move away from local optima. Extensive computational experiments validate that the ISSA outperforms other existing algorithms in solving the EFJSP due to the advantages of intensification and diversification mechanisms in the ISSA.

Electron irradiation total ionizing dose (TID) effect of tunneling magnetoresistance sensors

Tunnel magnetoresistance (TMR) sensors are rapidly gaining attention for magnetic field sensing applications owing to their high sensitivity, low power consumption, small size, and low cost. Their metallic, non-semiconductor construction makes them excellent candidates for use in the harsh environments present in nuclear and space applications. In this work, the impacts of electron irradiation on the magnetoelectric transport properties of the two types of TMR sensors were investigated. The electron fluence ranged from 0 Mrad(Si) to 400 Mrad(Si). No significant evidence of degradation of the sensor characteristics, such as sensitivity, resistance, TMR ratio and detectivity, was observed. Our results verify the robustness and adaptability of the TMR sensors.

A Low-Power Area-Efficient Precision Scalable Multiplier with an Input Vector Systolic Structure

In this paper, a small-area low-power 64-bit integer multiplier is presented, which is suitable for portable devices or wireless applications. To save the area cost and power consumption, an input vector systolic (IVS) structure is proposed based on four 16-bit radix-8 Booth multipliers and a data input scheme is proposed to reduce the number of signal transitions. This structure is similar to a systolic array in matrix multiply units of a Convolutional Neural Network (CNN), but it reduces the number of processing elements by 3/4 concerning the same vector systolic accelerator in reference. The comparison results prove that the IVS multiplier reduces at least 61.9% of the area and 45.18% of the power over its counterparts. To increase the hardware resource utilization, a Transverse Carry Array (TCA) structure for Partial Products Accumulation (PPA) was designed by replacing the 32-bit adders with 3/17-bit adders in the 16-bit multipliers. The experiment results show that the optimization could lead to at least a 6.32% and 13.65% reduction in power consumption and area cost, respectively, compared to the standard 16-bit radix-8 Booth multiplier. In the end, the precise scale of the proposed IVS multiplier is discussed. Benefiting from the modular design, the IVS multiplier can be configured to support sixteen different kinds of multiplications at a step of 16 bits [16b, 32b, 48b, 64b] × [16b, 32b, 48b, 64b].