Average Total Power Consumption Research Articles

Cascaded subarray design and control method for power efficient, thermal crosstalk optimized optical phased array.

Thermo-optic phase shifters (TOPSs) are commonly used in large-scale silicon photonic integrated optical phased arrays (OPAs). However, fast-response TOPSs consume relatively high power; the elevated temperature floor in the dense region of the TOPSs introduces thermal crosstalk between optical paths, which undermines the control accuracy. We propose a combined method that involves subarray design in the optical power distribution network and array control method to predict, optimize, and redistribute the phase shifts and mitigates thermal crosstalk. Thermal simulations and an array control method for generic OPA models are discussed. A silicon photonic chip prototype of a 4 × 4 OPA with three-level cascaded subarrays is fabricated to demonstrate the proposed method. The experimental and statistical results show that the method effectively reduces the average total power consumption by 31%, the maximum local temperature by 18.4%, and the thermal crosstalk within the OPA.

Robust Energy-Efficient Transmission for Cell-Free Massive MIMO Systems with Imperfect CSI

In this paper, we investigate a long-term power minimization problem of cell-free massive multiple-input multiple-output (MIMO) systems. To address this issue and to ensure the system queue stability, we formulate a dynamic optimization problem aiming to minimize the average total power cost in a time-varying system under imperfect channel conditions. The problem is then converted into a real-time weighted sum rate maximization problem for each time slot using the Lyapunov optimization technique. We employ approximation techniques to design robust sparse beamforming, which enables energy savings of the network and mitigates channel uncertainty. By applying direct fractional programming (DFP) and alternating optimization, we can obtain a locally optimal solution. Our DFP-based algorithm minimizes the average total power consumption of the network while satisfying the quality of service requirements for each user. Simulation results demonstrate the rapid convergence of the proposed algorithm and illustrate the tradeoff between average network power consumption and queue latency.

Finite-Time Thermodynamic Modeling and Analysis of Seawater Acidification Process in Electrochemical Acidification Cell.

The unsteady process of the acidification of seawater by using an electrochemical acidification cell (EAC) is studied in this paper. The model of the concentration of hydrogen ions () in the effluent seawater and the cell voltage of EAC varying with time and working current are built by applying the theory of finite-time thermodynamics, respectively. The semi-empirical formulas of the concentration of in the effluent seawater and the cell voltage under the constant current of the Ionpure EAC are obtained, respectively, by fitting the experimental data of the Ionpure EAC. Then, the simulated data are compared with the experimental data. The total work consumption and average power consumption of the Ionpure EAC are obtained from the semi-empirical formulas. The results show that the semi-empirical formulas can simulate the operation process of the Ionpure EAC well. The validity of the models is verified. The increase of the working current will increase the total work consumption and average power consumption of the Ionpure EAC. The proper current can be selected in engineering practice to achieve different goals, such as high efficiency or low energy consumption. The obtained results can provide some guidelines for the optimal design and optimization of EAC.

국내 데이터센터 폐열잠재량 산정에 관한 연구

The waste heat potential of data centers is attracting attention as a new heat energy source. In this study, waste heat potentials of domestic data centers were calculated and monthly potentials were predicted. The amount of potential was calculated from annual average total power consumption, PUE values of 10 data centers through surveys, and 66 domestic data center from ITSA (Korea Information Technology Service Industry Association). The waste heat potential was derived by considering the COP of the heat pump, excluding the amount of electricity from the compressor for recovery energy. Based on 10 data centers from surveys, the average potential ranged from 54,414,495 kWh to 65,075,294 kWh with respect to COP of chiller. The highest waste heat potential was 200,463,808 kWh. When the value of waste heat generated was examined by region, Gyeonggi Province had the highest value of 3,161,288,865 kWh among 66 domestic data centers. The waste heat potential from the data center was also predicted using TRNSYS modelling. The prediction error ranged from 9.04 to 32.85% for S data center located in Daejeon.

Load-Distribution-Based Trajectory Planning and Control for a Multilift System

This paper studies a load-distribution-based trajectory planning and control strategy for a hierarchically controlled multilift system. It proposes a method that simultaneously plans payload trajectory and cable forces while satisfying path and force constraints and minimizing the difference in cable forces. A direct collocation method is used to solve the formulated planning problem. Then, a neighboring feedback law is designed to equalize the cable tension load distribution during flight. Here, the system dynamics are linearized about the nominal path. An linear-quadratic regulator (LQR) controller is then designed for the system to track the planned trajectory. Simulations of payload transport showed that even with the effect of disturbances (i.e., wind gusts), cable tensions are more evenly distributed with the proposed approach. Finally, indoor flight tests were performed to validate the proposed approach. Results showed that the system has reduced energy consumption compared with the case without planning based on load distribution. The rotorcraft achieved less average total power and near-equal energy consumption.

A configurable fluorescence sensing front-end for ultra-low power and high sensitivity applications

This paper presents an ultra-low power, high sensitivity configurable CMOS fluorescence sensing front-end for implantable biosensors at single-cell level measurements. The front-end is configurable by a set of switches and consists of three integrated photodiodes (PD), three transimpedance amplifiers (TIA) for detecting a current range between 1 pA up to 10 mA. Also, an ambient light canceling technique is proposed to make the sensor operate under different environmental conditions. The proposed front-end could be configured for ultra-low light detection or ultra-low power consumption. The circuit is designed and fabricated in a 0.35 µm standard CMOS technology, and the measurement results are presented. The minimum integrated input-referred current noise is measured as 1.07 pA with the total average power consumption of 61.8 µW at an excitation frequency of 80 Hz. For ultra-low-power configuration, the front-end has an average power consumption of 119 nW and input integrated current noise of 210 pA at an excitation frequency of 20 kHz.

Multi-objective fault-tolerant optimization algorithm for deployment of IoT applications on fog computing infrastructure

Nowadays, fog computing as a complementary facility of cloud computing has attracted great attentions in research communities because it has extraordinary potential to provide resources and processing services requested for applications at the edge network near to users. Recent researchers focus on how efficiently engage edge networks capabilities for execution and supporting of IoT applications and associated requirement. However, inefficient deployment of applications’ components on fog computing infrastructure results bandwidth and resource wastage, maximum power consumption, and unpleasant quality of service (QoS) level. This paper considers reduction of bandwidth wastage in regards to application components dependency in their distributed deployment. On the other hand, the service reliability is declined if an application’s components are deployed on a single node for the sake of power consumption management viewpoint. Therefore, a mechanism for tackling single point of failure and application reliability enhancement against failure are presented. Then, the components deployment is formulated to a multi-objective optimization problem with minimization perspective of both power consumption and total latency between each pair of components associated to applications. To solve this combinatorial optimization problem, a multi-objective cuckoo search algorithm (MOCSA) is presented. To validate the work, this algorithm is assessed in different conditions against some state-of the arts. The simulation results prove the amount 42%, 29%, 46%, 13%, and 5% improvement of proposed MOCSA in terms of average overall latency respectively against MOGWO, MOGWO-I, MOPSO, MOBA, and NSGA-II algorithms. Also, in term of average total power consumption the improvement is about 43%, 28%, 41%, 30%, and 32% respectively.

RIATA: A Reinforcement Learning-Based Intelligent Routing Update Scheme for Future Generation IoT Networks

Future generation Internet of Things (IoT) communication infrastructure is expected to pave the path for innovative applications like smart cities, smart grids, smart industries, and smart healthcare. To support these diverse applications, the communication protocols are required to be adaptive and intelligent. At the network layer, an efficient and lightweight algorithm known as trickle-timer is designed to perform the route updates and it utilizes control messages to share the updated route information between IoT nodes. Trickle-timer tends to generate higher control overhead ratio and achieves lower reliability. Therefore, this article aims to propose an RL-based Intelligent Adaptive Trickle-Timer Algorithm (RIATA). The proposed algorithm performs three-fold optimization of the trickle-timer algorithm. Firstly, the RIATA assigns higher probability to control message transmission to nodes that have received an inconsistent control message in the past intervals. Secondly, the RIATA utilizes RL to learn the optimal policy to transmit or suppress a control message in the current network environment. Lastly, the RIATA selects an adaptive redundancy constant value to avoid unnecessary transmissions of control messages. Simulation results show that RIATA outperforms the other state-of-the-art mechanisms in terms of reducing control overhead ratio by an average of 21%, decreasing the average total power consumption by 10%, and increasing the packet delivery ratio by 4% on an average.

A Capacitive Pressure Sensor Interface IC with Wireless Power and Data Transfer.

This paper presents a capacitive pressure sensor interface circuit design in 180 nm XH018 CMOS technology for an implantable capacitive pressure sensor, which has a wireless power supply and wireless data transfer function. It integrates full-bridge rectifiers, shorting control switches, low-dropout regulators, bandgap references, analog front end, single slope analog to digital converter (ADC), I2C, and an RC oscillator. The low-dropout regulators regulate the wireless power supply coming from the rectifier and provide a stable and accurate 1.8 V DC voltage to other blocks. The capacitance of the pressure sensor is sampled to a discrete voltage by the analog front end. The single slope ADC converts the discrete voltage into 11 bits of digital data, which is then converted into 1 kbps serial data out by the I2C block. The “1” of serial data is modulated to a 500 kHz digital signal that is used to control the shorting switch for wireless data transfer via inductive back scatter. This capacitive pressure sensor interface IC has a resolution of 0.98 mmHg (1.4 fF), average total power consumption of 7.8 mW, and ±3.2% accuracy at the worst case under a −20 to 80 °C temperature range, which improves to ±0.86% when operated between 20 and 60 °C.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Summary As the share of variable renewable energy (VRE) grows in the electric grid, so does the risk of curtailment. While energy storage and hydrogen production have been proposed as solutions to the curtailment problem, they often pose technological and economic challenges. Here, we analyze the potential of data center load migration for mitigating curtailment and greenhouse gas (GHG) emissions. Using historical hourly electricity generation, curtailment, and typical data center server utilization data, we simulate the effect of migrating data center workloads from the fossil-fuel-heavy PJM to the renewable-heavy CAISO. The results show that load migration within the existing data center capacity during the curtailment hours in CAISO has the potential to reduce 113–239 KtCO2e per year of GHG emissions and absorb up to 62% of the total curtailment with negative abatement costs in 2019. Our study demonstrates the overlooked role that data centers can play for VRE integration and GHG emissions mitigation.

Stochastic Power Saving for Macrocell-Assisted Small Cell Networks

In this paper, a power saving scheme is investigated for macrocell-assisted small cell networks in the downlink, in which small cells are selected to stay in sleep or wake-up modes in order to mitigate excessive power consumption and the small cells operating in the sleep mode are eligible to off-load their served users to the macrocell to preserve communications. By taking the dynamics of user arrival into account, we attempt to minimize the average total power consumption of the network, which depends on several network parameters like power consumption of base stations, available bandwidth, user load in the cells, cell size, user rate requirement, rate outage probability and noise power density, while ensuring the average number of dropping off-loaded users to a satisfactory level. The design problem is then formulated as a constrained Markov decision process and solved via linear programming. A randomized strategy is proposed to accomplish the optimal sleep/wake-up policy for small cells. Simulation results confirm the effectiveness of the proposed scheme, as compared with the one without adopting sleep/wake-up mechanisms, and help us to capture the impact of the network parameters on the entire power saving.

Design of a passive CMOS implantable continuous monitoring biosensors transponder front-end

This paper presents the design of an implantable passive transponder front-end that can power implantable biosensors and also provide a power-efficient communication means for it with an extracorporeal reader, enabling continuous real-time monitoring of internal body parameters. The implantable passive transponder front-end is composed of power management circuity, demodulator, oscillator, and load-shift keying modulator. To control and power the implantable biosensors we used a 13.56 MHz Pulse Width Modulated signal. A stable DC voltage, data and clock are extracted from this modulated signal. The proposed transponder was designed, simulated and layout in a 40-nm 1P9M TSMC's CMOS technology. The simulation shows that the proposed implantable passive transponder front-end has a total average power consumption of 17.14 μW, with receiving data rate of 142.85 kB/s and transmitting data rate of 50 kB/s.

Non-Uniform Deployment of Power Beacons in Wireless Powered Communication Networks

In wireless powered communication networks (WPCNs), base station (BS) and power beacons (PBs) can offer supplement power for uplink transmission of user equipments (UEs). However, the aggregate power consumption of massively deployed PBs may exceed that of a BS. We propose a non-uniform deployment scheme for PBs in WPCNs, where a cell is divided into inner and outer areas, such that BS and PBs can cooperate to power UEs. To be more specific, a BS located in the center of a cell provides downlink power supply for the inner area UEs and uplink information decoding for all the UEs in the cell; while the PBs power UEs in the outer area. With multiple antennas, maximum ratio transmission and maximum ratio combining are adopted for downlink energy beamforming and uplink information reception. Considering a finite area of the network, we derive the distribution of the distance from a non-center-located UE to its nearest PB in the outer area. An optimization problem is formulated to minimize total average power consumption while satisfying BS average transmission power constraint and coverage probability threshold. Moreover, coverage probability is derived for performance evaluation. The numerical results show that the power consumption of the proposed scheme is reduced significantly compared to PB-only WPCNs.

Optimal Power and Performance Management for Heterogeneous and Arbitrary Cloud Servers

We investigate optimal power and performance management for heterogeneous and arbitrary cloud servers in a data center. In particular, we study the problems of power-constrained performance optimization and performance-constrained power optimization in a data center with multiple heterogeneous and arbitrary servers. These problems are essential to find optimal server speeds, such that: 1) the average task response time is minimized, and that the total power consumption does not exceed certain power constraint or 2) the total power consumption is minimized, and that the average task response time does not exceed certain performance constraint. Each server is treated as a G/G/1 queuing system, whose task interarrival times and task execution requirements can have arbitrary probability distributions. Furthermore, these servers are entirely heterogeneous in terms of task interarrival time, task execution requirement, and power consumption models. The main contributions of this paper are summarized as follows: 1) we formulate the average task response time as well as the total power consumption in a data center with multiple heterogeneous and arbitrary servers as the functions of server speeds; 2) we define our optimization problems by finding optimal server speeds, since the server speeds determine both the average task response time and total power consumption; 3) we develop algorithms to find the optimal solutions and demonstrate numerical data; and 4) we also develop several closed-form heuristic solutions and compare their quality with that of the optimal solution. Our approach provides an analytical way of studying the power-performance tradeoff at the data center level.

High-Speed Serializer for a 64 GS s−1 Digital-to-Analog Converter in a 28 nm Fully-Depleted Silicon-on-Insulator CMOS Technology

Abstract. An attractive solution to provide several channels with very high data rates of tens of Gbit s−1 for digital-to-analog converters (DACs) in arbitrary waveform generators (AWGs) is to use a high speed serializer in front of the DAC. As data sources, on-chip memories, digital signal processors or field-programmable gate arrays can be used. Here, we present a serializer consisting of a 19 channel 16:1 multiplexer (MUX) for output data rates up to 64 Gbit s−1 per channel and a low skew (∼ 8.8 ps) two-phase frequency divider and clock distribution network that is completely realized in static CMOS logic. The circuit is designed in a 28 nm Fully-Depleted Silicon-on-Insulator (FD-SOI) technology and will be used in an 8 bit 64 GS s−1 DAC between the on-chip memory and the DAC output stage. Due to a four bits unary and four bits binary segmentation, a 19 channel MUX is required. Simulations on layout level reveal a data-dependent peak-to-peak jitter of less than 1.8 ps at the output of one MUX channel with a total average power consumption of approximately 1.15 W of the whole MUX and clock network.

Ultra-Low Power High Stability 8T SRAM for Application in Object Tracking System

In this paper, an ultra-low power (ULP) 8T static random access memory (SRAM) is proposed. The proposed SRAM shows better results as compared with conventional SRAMs in terms of leakage power, write static noise margin, write-ability, read margin, and $I_{ \mathrm{\scriptscriptstyle ON}}/I_{ \mathrm{\scriptscriptstyle OFF}}$ . It is observed that the leakage power is reduced to $82\times $ (times) and $75\times $ as compared with the conventional 6T SRAM and read decoupled (RD)-8T SRAM, respectively, at 300 mV VDD. In addition, write static noise margin (WSNM), write trip point (WTP), read dynamic noise margin, and $I_{ \mathrm{\scriptscriptstyle ON}}/I_{ \mathrm{\scriptscriptstyle OFF}}$ ratio are also improved by 7.1%, 43%, 7.4%, and $74\times $ than conventional 6T SRAM, respectively, at 0.3 V VDD. Moreover, the WSNM, WTP, and $I_{ \mathrm{\scriptscriptstyle ON}}/I_{ \mathrm{\scriptscriptstyle OFF}}$ values are improved by 6.67%, 7.14%, and $68\times $ as compared with RD-8T SRAM, respectively, at 0.3 V VDD. Furthermore, a fast, reliable, less memory usage object tracking algorithm and implementation of its memory block using ULP 8T SRAM are proposed. A quadtree-based approach is employed to diminish the bounding box and to reduce the computations for fast and low power object tracking. This, in turn, minimizes the complexity of the algorithm and reduces the memory requirement for tracking. The proposed object detection and tracking method are based on macroblock resizing, which demonstrates an accuracy rate of 96.5%. In addition, the average total power consumption for object detection and tracking which includes writing, read and hold power is $1.63\times $ and $1.45\times $ lesser than C6T and RD8T SRAM at 0.3 V VDD.

Multilevel Supply-Modulated Chireix Outphasing With Continuous Input Modulation

This paper presents a dynamic characterization of a multilevel (ML) Chireix outphasing (ML-CO) power amplifier (PA) with modulated signals. The ML-CO technique combines the advantages of envelope tracking and outphasing architectures by limiting the supply modulation to discrete levels with an efficient power-DAC modulator and using outphasing for fine amplitude control. We describe an experimental test bench that supplies the required phase- and time-aligned modulated signals for outphasing and supply modulation simultaneously. Pulsed characterization is used to design an ML memoryless polynomial DPD. The linearized ML-CO GaN X-band MMIC PA is demonstrated with fixed input drive levels for 9.3-dB peak-to-average power ratio (PAPR), 1.4-MHz and 11.3-dB PAPR, 10-MHz LTE signals with a 9.7-GHz carrier. For both signals, the average total power consumption is reduced by a factor of two when supply modulation is used. An investigation of control signal generation strategies is presented, including combinations of discrete supply and continuous input modulation. A simple exponential function tracks the optimal efficiency trajectory of the ML-CO PA, enabling overall efficiency improvements within 9 and 27 percentage points. This control strategy is applied to radar pulses with amplitude shaping and frequency chirp, with the efficiency improvement of up to 11.8 percentage points compared with constant-supply operation, with 29-dB improvement in spectral confinement.

Energy efficiency-QoS relation and its application in wireless networks

Since improving energy efficiency (EE) must not sacrifice quality-of-service (QoS), the EE-QoS relation is a fundamental issue for EE optimization. This paper provides an overview of our research on the EE-QoS relation and its application to elastic access optimization in hyper-cellular networks over the past five years. Because delay bound is a representative QoS requirement, we first discuss our findings on the EE-delay relation, and show that if average total power consumption is linear with average service rate, then there exists a non-tradeoff region in the EE-delay relationship. We then summarize how to design energy efficient resource allocation for different kinds of services, such as real-time and non-real-time services, and ultra-reliable and ultra-low latency service. For real-time service, in order to achieve the optimal EE-delay relation, resource allocation should depend on queue length. For delay tolerant service, it is possible to leverage predictive information for making a resource allocation plan and pushing data. The results show that the trajectories and preferences of users are very useful for improving EE in wireless systems. Finally, we summarize preliminary results for the resources required to maximize EE under the constraints of ultra-reliable and low-latency network.

Analytical framework for power saving evaluation in two-tier heterogeneous mobile networks

Reducing the power consumption of base stations in mobile networks is an important issue. We investigate the power saving evaluation in two-tier heterogeneous mobile networks which consist of femtocells overlaid by macrocells. In the heterogeneous mobile networks, base stations without traffic load are allowed to enter the sleep mode to save power. The power saving probability that a base station enters the sleep mode and the average total power consumption of this network are complex joint-effects of various factors. Successful modelling of these complex joint-effects is critical to mobile network operators when they pursue the design of green mobile networks. In this paper we propose an analytical framework to facilitate systematic analysis. Based on the proposed analytical framework, we investigate the power saving probabilities and the average total power consumption in terms of several parameters, including the new traffic arrival rate per user, the maximum transmission power of a femtocell, the number of femtocells within a macrocell, and the number of users in the network. Numerical results show that the proposed analytical framework provides a useful and efficient method to facilitate systematic analysis and design of green mobile networks. Simulation results validate the accuracy of the proposed analytical framework.

Throughput-Optimal Link-Layer Design in Power Constrained Hybrid OW/RF Systems

The aim of this paper is to develop link layer transmission schemes for hybrid optical wireless (OW)/radio frequency (RF) systems, with constraints on both per-link and total average power consumption at the transmitter. In this context, we adopt a timeslot structure with a queue for storing the data packets for transmission and model the hybrid channel as an erasure channel with parameters varying along the time-slots according to a Markov chain. Then, a stochastic optimization problem is formulated, where intelligent decisions regarding the number of the packets admitted in the queue and the power levels used in every link, are taken by the hybrid transmitter in each slot. The objective of this formulation is to design a control policy that maximizes the transmitter throughput, while satisfying the power constraints as well. A solution is offered by using the Lyapunov optimization framework and an on-line transmission algorithm is developed. The proposed transmission algorithm takes decisions based only on the status of the queue and the statistical parameters of the OW/RF channel in each time-slot, without requiring any knowledge of the underlying Markov chain of the channel process, or the statistics of the packet arrival process. Furthermore, in order to alleviate the requirement for full feedback at the transmitter, i.e., feedback for every successfully received packet, which is critical for the accurate queue update, we extend our analysis and incorporate reduced-feedback coding schemes. The proposed transmission policy in this scenario still meets the throughput objective and satisfies the power consumption constraints, while a tradeoff between transmission delays and feedback requirements is revealed.