Performance Analysis of Data Organization of the Real-Time Memory Database Based on Red-Black Tree

Author(s):  
Liang Qiaoyu ◽  
Li Jianwei ◽  
Xu Yubin
2012 ◽  
Vol 512-515 ◽  
pp. 2670-2675
Author(s):  
Yuan Bin Yu ◽  
Hai Tao Min ◽  
Xiao Dong Qu ◽  
Jun Guo

μC/OS-II is one of RTOS which has remarkable advantages, such as high reliability, high real-time ability, and easy code scalability. This paper transplanted it into BMS on electric vehicle successfully which was based on MC9S12XDP512 MCU hardware platform. Using quantitative comparison under specific tests, this paper also verified the real-time and reliability advantages of μC/OS-II.


2017 ◽  
Author(s):  
A. Alom ◽  
B.A. Prabowo ◽  
P. Pal ◽  
M.K. Secario ◽  
P.-T. Ou ◽  
...  

2014 ◽  
Vol 6 ◽  
pp. 270749 ◽  
Author(s):  
Yingfeng Zhang ◽  
Wenbo Wang ◽  
Sichao Liu ◽  
Gongnan Xie

Typical challenges that manufacturing enterprises are facing now are compounded by lack of timely, accurate, and consistent information of manufacturing resources. As a result, it is difficult to analyze the real-time production performance for the shop-floor. In this paper, the definition and overall architecture of the internet of manufacturing things is presented to provide a new paradigm by extending the techniques of internet of things (IoT) to manufacturing field. Under this architecture, the real-time primitive events which occurred at different manufacturing things such as operators, machines, pallets, key materials, and so forth can be easily sensed. Based on these distributed primitive events, a critical event model is established to automatically analyze the real-time production performance. Here, the up-level production performance analysis is regarded as a series of critical events, and the real-time value of each critical event can be easily calculated according to the logical and sequence relationships among these multilevel events. Finally, a case study is used to illustrate how to apply the designed methods to analyze the real-time production performance.


2007 ◽  
Vol 51 (9) ◽  
pp. 2311-2325 ◽  
Author(s):  
Claudio Cicconetti ◽  
Luciano Lenzini ◽  
Enzo Mingozzi ◽  
Giovanni Stea

2014 ◽  
Author(s):  
Irving Biederman ◽  
Ori Amir
Keyword(s):  

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