scholarly journals Stochastic Power Consumption Model of Wireless Transceivers

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4704
Author(s):  
Paweł Kryszkiewicz ◽  
Adrian Kliks ◽  
Łukasz Kułacz ◽  
Bartosz Bossy
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Consumption ◽  
Random Variables ◽  
Specific Model ◽  
System Level ◽  
Model Parameters ◽  
Wireless Transceivers ◽  
Consumption Model ◽  
Wide Group

Energy efficiency is a key aspect when designing and optimizing contemporary wireless networks and transceivers. Assessment of energy efficiency requires proper energy consumption models. The most common solutions are to measure a single device and propose a device-specific model or to propose a simplified model for many transceivers but not reflecting all phenomena visible in a given transceiver energy consumption. Therefore, it has to be selected to accurately model a single transceiver or coarsely model a wide group of transceivers. This paper proposes a new approach, where a fixed energy consumption model is used but with parameters being random variables. This reflects variability between various transceivers from various vendors. First the model parameters are adjusted separately for each of 14 measured WiFi modems. These devices are treated as samples of a wider population of devices and their parameters are used for stochastic parameters modeling, i.e., choosing the random variables’ distributions, their parameters, and the correlation among parameters. The proposed model can be used, e.g., for system-level network design where variability among transceivers power consumption can be used as a new degree of freedom. The paper presents simulation results for a simple multi-hop link whose energy consumption is characterized in much more detail thanks to the proposed stochastic power consumption model.

scholarly journals Power and Performance Evaluation of Memory-Intensive Applications

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4089
Author(s):  
Kaiqiang Zhang ◽  
Dongyang Ou ◽  
Congfeng Jiang ◽  
Yeliang Qiu ◽  
Longchuan Yan
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Consumption ◽  
Job Scheduling ◽  
Memory System ◽  
Processor Core ◽  
Memory Efficiency ◽  
And Performance ◽  
Reasonable Use ◽  
Server System

In terms of power and energy consumption, DRAMs play a key role in a modern server system as well as processors. Although power-aware scheduling is based on the proportion of energy between DRAM and other components, when running memory-intensive applications, the energy consumption of the whole server system will be significantly affected by the non-energy proportion of DRAM. Furthermore, modern servers usually use NUMA architecture to replace the original SMP architecture to increase its memory bandwidth. It is of great significance to study the energy efficiency of these two different memory architectures. Therefore, in order to explore the power consumption characteristics of servers under memory-intensive workload, this paper evaluates the power consumption and performance of memory-intensive applications in different generations of real rack servers. Through analysis, we find that: (1) Workload intensity and concurrent execution threads affects server power consumption, but a fully utilized memory system may not necessarily bring good energy efficiency indicators. (2) Even if the memory system is not fully utilized, the memory capacity of each processor core has a significant impact on application performance and server power consumption. (3) When running memory-intensive applications, memory utilization is not always a good indicator of server power consumption. (4) The reasonable use of the NUMA architecture will improve the memory energy efficiency significantly. The experimental results show that reasonable use of NUMA architecture can improve memory efficiency by 16% compared with SMP architecture, while unreasonable use of NUMA architecture reduces memory efficiency by 13%. The findings we present in this paper provide useful insights and guidance for system designers and data center operators to help them in energy-efficiency-aware job scheduling and energy conservation.

scholarly journals Optimizing Power Consumption of Freight Railroad Bearings Using Laboratory Experimental Data

2020 ◽  
Author(s):  
Carlos E. Lopez ◽  
Constantine Tarawneh ◽  
Arturo Fuentes ◽  
Harry Siegal
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Consumption ◽  
Optimal Operating ◽  
Speed Condition ◽  
Load Train ◽  
Train Speed ◽  
Railroad Bearings ◽  
Railroad Bearing ◽  
The University

Abstract Based on projected freight truck fuel efficiency, freight railroad and equipment suppliers need to identify, evaluate and implement technologies and/or operating practices to maintain traditional railroad economic competitiveness. The railway industry uses systems that record the total energy efficiency of a train but not energy efficiency or consumption by components. Lowering the energy consumption of certain train components will result in an increase in its overall energy efficiency, which will yield cost benefits for all the stakeholders. One component of interest is the railroad bearing whose power consumption varies depending on several factors that include railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Being able to quantify the bearing power consumption, as a function of the variables mentioned earlier, would make it possible to obtain optimal operating condition ranges that minimize energy consumption and maximize train energy efficiency. Several theoretical studies were performed to estimate the power consumption within railroad bearings, but those studies lacked experimental validation. For almost a decade now, the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV) has been collecting power consumption data for railroad bearings under various loads, speeds, ambient temperatures, and bearing condition. The objective of this ongoing study is to use the experimentally acquired power consumption to come up with a correlation that can be used to quantify the bearing power consumption as a function of load, speed, ambient temperature, and bearing condition. Once obtained, the model can then be used to determine optimal operating practices that maximize the railroad bearing energy efficiency. In addition, the developed model will provide insight into possible areas of improvement for the next generation of energy efficient railroad bearings. This paper will discuss ongoing work including experimental setup and findings of energy consumption of bearings as function of railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Findings of energy consumption are converted into approximations of diesel gallons to quantify the effect of nominal energy consumption of the bearings and show economic value and environmental impact.

scholarly journals Energy Consumption Model for Drilling Processes Based on Cutting Force

2019 ◽  
Vol 9 (22) ◽  
pp. 4801
Author(s):  
Qi Wang ◽  
Dinghua Zhang ◽  
Bing Chen ◽  
Ying Zhang ◽  
Baohai Wu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Cutting Force ◽  
Drilling Process ◽  
Cutting Power ◽  
Energy Models ◽  
Auxiliary Power ◽  
Proposed Model ◽  
Energy Consumption Model ◽  
Consumption Model

Accurate energy consumption modelling is critical for the improvement of energy efficiency in machining. Existing energy models of machining processes mainly focus on turning or milling, and there are few energy models for drilling. However, since drilling is often applied to roughing and semi-finishing, and the cutting parameters are large, the energy consumption is huge, and it is urgent to study the consumption of energy during the drilling process. In this paper, an energy consumption model for drilling processes was proposed. Idle power, cutting power, and auxiliary power were included in the proposed energy consumption model, using the cutting force to obtain the cutting power during drilling. Further, the relationship between cutting power and auxiliary power was analyzed. Cutting experiments were then carried out which confirmed the correctness of the proposed model. In addition, compared with several existing energy consumption models, the proposed model had better accuracy and applicability. It is expected that the proposed energy consumption model will have applications for the minimization of energy consumption and improvement of energy efficiency but not limited to only drilling energy consumption prediction.

scholarly journals A DEVELOPMENT OF OPTICAL NETWORK UNIT POWER CONSUMPTION MODEL CONSIDERING TRAFFIC LOAD EFFECT

2018 ◽  
Vol 80 (4) ◽  
Author(s):  
Arnidza Ramli ◽  
Nadiatulhuda Zulkifli ◽  
Auwalu Usman ◽  
Sevia Mahdaliza Idrus
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Optical Network ◽  
Sampling Rate ◽  
Access Network ◽  
Passive Optical Network ◽  
Traffic Load ◽  
Optical Network Unit ◽  
Load Effect ◽  
Consumption Model

Accurate and precise measurement of energy consumption for the deployment of fiber-to-the-home (FTTH) network using Gigabit passive optical network (GPON) is vital to the research community to develop models for the synthesis of energy-efficient protocols and algorithms for the access network. However, lack of power consumption measurement of optical network devices in the past has led to unrealistic and/or oversimplified model being used in simulations. Usually the access network devices are assumed always on and their consumption is both traffic and time independent. Therefore, in this paper we propose an experimentally-driven approach to i) characterize the Optical Network Unit (ONU) from the power consumption standpoint and ii) develop more accurate power consumption model for the ONU. We focus on ONU since it represents the main contributor to the energy consumption of optical access network. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a GPON network testbed. The measurement is limited to a maximum 100 Mbps data rate due to a limitation in the sampling rate and precision of the measurement device. However, validation has been done with theoretical power consumption model in order to prove the feasibility of the proposed model. Our measurements show that the power consumption of the ONU exhibits a linear dependence on the traffic in which the power consumption at idle mode is 11.51 W while in low power mode the power consumption is around 7.52 W.

Energy Efficiency of Transmit Diversity Systems Under a Realistic Power Consumption Model

2013 ◽  
Vol 17 (1) ◽  
pp. 119-122 ◽  
Author(s):  
Marcos Tomio Kakitani ◽  
Glauber Brante ◽  
Richard Demo Souza ◽  
Muhammad Ali Imran
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Transmit Diversity ◽  
Diversity Systems ◽  
Consumption Model

scholarly journals Energy Efficiency of Multiple Antenna Cellular Networks Considering a Realistic Power Consumption Model

2019 ◽  
Vol 3 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Roberto Krauss ◽  
Glauber Brante ◽  
Ohara Kerusauskas Rayel ◽  
Richard Demo Souza ◽  
Oluwakayode Onireti ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Cellular Networks ◽  
Multiple Antenna ◽  
Consumption Model

scholarly journals Smart metering application for power efficiency studies

2015 ◽  
Vol 4 (1) ◽  
pp. 78
Author(s):  
Cristian Tudoran ◽  
Stefan Albert ◽  
Dorin N. Dadarlat ◽  
Carmen Tripon ◽  
Sorin Dan Anghel
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Consumption ◽  
Monitoring System ◽  
Data Center ◽  
Power Efficiency ◽  
Consumption Patterns ◽  
Smart Metering ◽  
Research Teams ◽  
Energy Consumption Patterns

Improving the energy efficiency of our Institute’s data center is an ambitious challenge for our research teams. Understanding how the energy is consumed in each segment of the system becomes fundamental in order to minimize the overall energy consumed by the system itself. In this paper, we propose an experimentally–driven approach to develop a simple and accurate power consumption and temperature monitoring system. In this work we focused our attention on the monitoring, measurement of the energy consumption patterns of our data center system, at INCDTIM Cluj-Napoca, Romania.

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