scholarly journals LTE UE Power Consumption Model: For System Level Energy and Performance Optimization

2012 ◽  
Author(s):  
Anders R. Jensen ◽  
Mads Lauridsen ◽  
Preben Mogensen ◽  
Troels B. Sørensen ◽  
Per Jensen
Keyword(s):  
Power Consumption ◽  
Performance Optimization ◽  
System Level ◽  
Level Energy ◽  
Consumption Model ◽  
And Performance

System-level energy and performance projections for nanomagnet-based logic

2009 ◽  
Author(s):  
Aaron Dingler ◽  
Michael Niemier ◽  
X. Sharon Hu ◽  
Michael Garrison ◽  
M. Tanvir Alam
Keyword(s):  
System Level ◽  
Level Energy ◽  
And Performance

Power and Performance Based Genetic Ant Colony Algorithm for Virtual Machine Placement

2020 ◽  
Vol 17 (1) ◽  
pp. 32-36
Author(s):  
Sushmitha ◽  
G. M. Karthik ◽  
M. Sayeekumar
Keyword(s):  
Power Consumption ◽  
Virtual Machine ◽  
Data Center ◽  
Ant Colony Algorithm ◽  
Virtual Machines ◽  
Virtual Machine Placement ◽  
The Internet ◽  
Computing Services ◽  
Consumption Model ◽  
And Performance

Cloud Computing is the provisioning of computing services over the Internet. A Virtual Machine (VM) creation request has to be processed in any one data center of the physical machines. Virtual Machine Placement refers to choosing appropriate host for the VM. One of the major concerns in datacenter management is reducing the power consumption and performance filth of virtual machines. For solving the problem, GACO algorithm is proposed which uses PpW, IPR and LDR as heuristic information for ACO algorithm and for selection in Genetic algorithm. It also uses a non-linear power consumption model for quantifying power. The performance evaluation shows the efficiency of the algorithm.

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 optimization at the system level

2005 ◽  
Author(s):  
Valentina Salapura ◽  
Manish Gupta ◽  
Shawn Hall ◽  
Ruud A. Haring ◽  
Philip Heidelberger ◽  
...  
Keyword(s):  
Performance Optimization ◽  
System Level ◽  
And Performance
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