scholarly journals Focus on Energy Efficiency Through Power Consumption Disaggregation

10.5772/59311 ◽  
2015 ◽  
Author(s):  
Rodrigo M. Bacurau ◽  
Luís F.C. Duarte ◽  
Elnatan C. Ferreira
Keyword(s):  
Energy Efficiency ◽  
Power Consumption

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 Massive MIMO: Achievable Energy Efficiency for 5G systems with Multi-user Environment

2019 ◽  
Vol 8 (2) ◽  
pp. 6527-6534
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Path Loss ◽  
Antenna System ◽  
Base Station ◽  
Small Cells ◽  
Limiting Factors ◽  
Improve Energy Efficiency ◽  
User Terminal ◽  
Simulation Results

Massive Multi-Input and Multi-Output (MIMO) antenna system potentially provides a promising solution to improve energy efficiency (EE) for 5G wireless systems. The aim of this paper is to enhance EE and its limiting factors are explored. The maximum EE of 48 Mbit/Joule was achieved with 15 user terminal (UT)s. This problem is related to the uplink spectral efficiency with upper bound for future wireless networks. The maximal EE is obtained by optimizing a number of base station (BS) antennas, pilot reuse factor, and BSs density. We presented a power consumption model by deriving Shannon capacity calculations with closed-form expressions. The simulation result highlights the EE maximization with optimizing variables of circuit power consumption, hardware impairments, and path-loss exponent. Small cells achieve high EE and saturate to a constant value with BSs density. The MRC scheme achieves maximum EE of 36 Mbit/Joule with 12 UTs. The simulation results show that peak EE is obtained by deploying massive BS antennas, where the interference and pilot contamination are mitigated by coherent processing. The simulation results were implemented by using MATLAB 2018b.

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 SNMP for Cloud Environment Energy Efficiency

2021 ◽  
Author(s):  
Marta Chinnici ◽  
Asif Iqbal ◽  
ah lian kor ◽  
colin pattinson ◽  
eric rondeau
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Power Consumption ◽  
Empirical Evidence ◽  
Rapid Growth ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Second Stage ◽  
The Core ◽  
Snmp Protocol

Abstract Cloud computing has seen rapid growth and environments are now providing multiple physical servers with several virtual machines running on those servers. Networks have grown larger and have become more powerful in recent years. A vital problem related to this advancement is that it has become increasingly complex to manage networks. SNMP is one standard which is applied as a solution to this management of networks problem. This work utilizes SNMP to explore the capabilities of SNMP protocol and its features for monitoring, control and automation of virtual machines and hypervisors. For this target, a stage-wise solution has been formed that obtains results of experiments from the first stage uses SNMPv3 and feed to the second stage for further processing and advancement. The target of the controlling experiments is to explore the extent of SNMP capability in the control of virtual machines running in a hypervisor, also in terms of energy efficiency. The core contribution based on real experiments is conducted to provide empirical evidence for the relation between power consumption and virtual machines.

Energy Efficient Refrigerators: The Effect of Door Gasket and Wall Insulation on Heat Transfer

2003 ◽  
Author(s):  
Mir-Akbar Hessami ◽  
Arnd Hilligweg
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Energy Efficiency ◽  
Power Consumption ◽  
Thermal Efficiency ◽  
Air Temperatures ◽  
Insulation Thickness ◽  
Two Stages ◽  
Experimental Rig ◽  
The Doors

The energy efficiency of refrigerators not only depends on the efficiency of the various components used in the cycle but also on their thermodynamics cycle efficiency as well the thermal efficiency of the cabinet housing the components. Efficiency improvements to the thermodynamics cycle and refrigerator components have been the subject of various papers published in the open literature. Not many researchers have looked at reducing the heat leakage into the refrigerator cabinet with the explicit objective of reducing the power consumption of the unit and hence improving its thermal efficiency. This paper is based on an experimental study of this topic, and includes information on the experimental rig used and the results obtained. This research was performed in two stages: The first stage was focused on improving the energy efficiency by changing wall insulation while the second stage was to study the heat transfer through the doors’ gaskets. For the first part, a domestic refrigerator was instrumented with many thermocouples and heat flux meters to measure the inside and outside air temperatures and the heat transfer through the wall of the unit, respectively. These measurements were taken under different environmental conditions as well as different insulation thickness in the walls of the cabinet. For the second part, using a specially designed and manufactured experimental rig, various door gaskets were placed between a warm and a cold chamber and heat transfer through the gasket was measured. The results showed that by adding 30 mm polystyrene insulation to the walls of the refrigerator, the heat transfer through the walls reduced by around 35%. The power consumption data agreed very well with the measured heat flux through the walls. The percentage heat transfer through the doors’ gaskets was confirmed to be about 13% of the total heat transferred into the unit.

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