scholarly journals Minimizing energy consumption of accelerators and storage ring facilities

1980 ◽  
Author(s):  
M. Q. Barton ◽  
H. Gerke ◽  
G. A. Loew ◽  
R. A. Lundy ◽  
W. Schnell
Keyword(s):  
Energy Consumption ◽  
Storage Ring ◽  
And Storage

Scientific program of DERICA — prospective accelerator and storage ring facility for radioactive ion beam research

2018 ◽  
Vol 189 (07) ◽  
pp. 721-738
Author(s):  
Leonid V. Grigorenko ◽  
Boris Yu. Sharkov ◽  
Andrei S. Fomichev ◽  
Aleksei L. Barabanov ◽  
V. Bart ◽  
...  
Keyword(s):  
Storage Ring ◽  
Ion Beam ◽  
Scientific Program ◽  
Radioactive Ion Beam ◽  
And Storage

scholarly journals The new injector and storage ring for the MAX-laboratory

1999 ◽  
Author(s):  
S. Werin ◽  
A. Andersson ◽  
M. Eriksson ◽  
M. Georgsson ◽  
G. LeBlanc ◽  
...  
Keyword(s):  
Storage Ring ◽  
And Storage

scholarly journals Optimal Offloading Decision Strategies and Their Influence Analysis of Mobile Edge Computing

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3231 ◽  
Author(s):  
Jiuyun Xu ◽  
Zhuangyuan Hao ◽  
Xiaoting Sun
Keyword(s):  
Energy Consumption ◽  
Time Delay ◽  
Branch And Bound ◽  
Edge Computing ◽  
Optimal Decision ◽  
Mobile Edge Computing ◽  
Wireless Devices ◽  
Influence Analysis ◽  
Cloud Servers ◽  
And Storage

Mobile edge computing (MEC) has become more popular both in academia and industry. Currently, with the help of edge servers and cloud servers, it is one of the substantial technologies to overcome the latency between cloud server and wireless device, computation capability and storage shortage of wireless devices. In mobile edge computing, wireless devices take responsibility with input data. At the same time, edge servers and cloud servers take charge of computation and storage. However, until now, how to balance the power consumption of edge devices and time delay has not been well addressed in mobile edge computing. In this paper, we focus on strategies of the task offloading decision and the influence analysis of offloading decisions on different environments. Firstly, we propose a system model considering both energy consumption and time delay and formulate it into an optimization problem. Then, we employ two algorithms—Enumerating and Branch-and-Bound—to get the optimal or near-optimal decision for minimizing the system cost including the time delay and energy consumption. Furthermore, we compare the performance between two algorithms and draw the conclusion that the comprehensive performance of Branch-and-Bound algorithm is better than that of the other. Finally, we analyse the influence factors of optimal offloading decisions and the minimum cost in detail by changing key parameters.

Cabling design of booster and storage ring construction progress of TPS

2017 ◽  
Vol 12 (06) ◽  
pp. P06011-P06011
Author(s):  
Y.-S. Wong ◽  
K.-B. Liu ◽  
C.-Y. Liu ◽  
b.-S. Wang
Keyword(s):  
Storage Ring ◽  
And Storage

The Construction and Practice of Energy Consumption Management System for Coal-Fired Power Plant

2013 ◽  
Vol 448-453 ◽  
pp. 2781-2785
Author(s):  
Zhe Li ◽  
Yun Liang ◽  
Jian Wei Ma ◽  
Ping Zhang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Remote Monitoring ◽  
Emission Reduction ◽  
Data Transfer ◽  
Electric Power Industry ◽  
Reliable Data ◽  
Smart Device ◽  
Rapid Modeling ◽  
And Storage

Electric power industry is of great potential on energy saving and emission reduction. Remote monitoring and analyzing on the energy consumption of coal-fired units is important methods and basis for energy saving. The system was developed a data acquisition smart device to acquire the energy consumption parameters, designed the cogeneration units "exceed power" algorithm and the energy consumption general model. The system satisfies the industrial requirements of accurate and reliable data transfer and storage and effectively enhances the rapid modeling capabilities, so as to provide technical support for the energy saving and emission reduction works.

A Distributed Data Storage Method Based on Integrated Threshold

2011 ◽  
Vol 268-270 ◽  
pp. 595-600
Author(s):  
Yi Liu
Keyword(s):  
Energy Consumption ◽  
Data Storage ◽  
Hot Spots ◽  
Group Analysis ◽  
Distributed Data ◽  
Distributed Data Storage ◽  
Storage Method ◽  
Consumption Data ◽  
And Storage ◽  
Failure Node

Based on the analysis and study of the data storage strategy in wireless sensor networks, this paper presents a distributed data storage method based on sleep scheduling to resolve the problems of network imbalance and storage hot spots problems.Finally, multi group analysis of simulate experiments results show that compared to other data storage method the distributed data storage method based on composite threshold have obviously advantages on the sides of overall energy consumption,data storage capacity,the number of failure node and data quality,thus have a significant effect on reducing energy consumption and extending network life cycle.

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