scholarly journals A Compile-Time Optimization Method for WCET Reduction in Real-Time Embedded Systems through Block Formation

2016 ◽  
Vol 12 (4) ◽  
pp. 1-25 ◽  
Author(s):  
Morteza Mohajjel Kafshdooz ◽  
Mohammadkazem Taram ◽  
Sepehr Assadi ◽  
Alireza Ejlali
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Optimization Method ◽  
Time Optimization ◽  
Block Formation

scholarly journals ADAPTIVE DISTRIBUTION OF A SWARM OF HETEROGENEOUS ROBOTS

2016 ◽  
Vol 56 (1) ◽  
pp. 67 ◽  
Author(s):  
Amanda Prorok ◽  
M. Ani Hsieh ◽  
Vijay Kumar
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Optimization Problem ◽  
Optimization Method ◽  
Transition Rates ◽  
Trait Distribution ◽  
Time Optimization ◽  
Heterogeneous Robots ◽  
Real Time Optimization ◽  
Optimal Set

We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type) is defined by the traits (capabilities) that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution is reached as quickly as possible. Since our method is based on the derivation of an analytical gradient, it is very efficient with respect to state-of-the-art methods. Building on this result, we propose a real-time optimization method that enables an online adaptation of transition rates. Our approach is well-suited for real-time applications that rely on online redistribution of large-scale robotic systems.

scholarly journals Power-conscious Scheduling for Real-time Embedded Systems Design

VLSI Design ◽  
2001 ◽  
Vol 12 (2) ◽  
pp. 139-150 ◽  
Author(s):  
Youngsoo Shin ◽  
Kiyoung Choi ◽  
Takayasu Sakurai
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Systems Design ◽  
Optimization Method ◽  
Efficient Design ◽  
Power Efficient ◽  
On Line ◽  
Time Variations ◽  
Processor Speed ◽  
Programmable Processors

Power efficient design of real-time embedded systems based on programmable processors becomes more important as system functionality is increasingly realized through software. We address a power optimization method for real-time embedded applications on a variable speed processor. The method combines off-line and on-line components. The off-line component determines the lowest possible maximum processor speed while guaranteeing deadlines of all tasks. The on-line component dynamically varies the processor speed or bring a processor into a power-down mode to exploit execution time variations and idle intervals. Experimental results show that the proposed method obtains a significant power reduction across several kinds of applications.

On-Board Real-Time Optimization Control for Turbo-Fan Engine Life Extending

2016 ◽  
Vol 0 (0) ◽  
Author(s):  
Qiangang Zheng ◽  
Haibo Zhang ◽  
Lizhen Miao ◽  
Fengyong Sun
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Support Vector ◽  
Thermal Mechanical Fatigue ◽  
Mechanical Fatigue ◽  
Time Optimization ◽  
Optimization Control ◽  
Conventional Optimization ◽  
Real Time Optimization ◽  
Engine Life

AbstractA real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.

Real-time Optimization Method for Optical Parameters of Ion Implanters

2006 ◽  
Author(s):  
Seiji Ogata ◽  
Tsutomu Nishihashi ◽  
Kazuhiko Tonari ◽  
Hidekazu Yokoo ◽  
Hideo Suzuki ◽  
...  
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Optical Parameters ◽  
Time Optimization ◽  
Real Time Optimization

scholarly journals A real-time optimization method for economic and effective operation of electrostatic precipitators

2020 ◽  
Vol 70 (7) ◽  
pp. 708-720
Author(s):  
Chenghang Zheng ◽  
Zhongyang Zhao ◽  
Yishan Guo ◽  
Haitao Zhao ◽  
Weiguo Weng ◽  
...  
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Time Optimization ◽  
Effective Operation ◽  
Electrostatic Precipitators ◽  
Real Time Optimization

scholarly journals A Novel Rail-Network Hardware Simulator for Embedded System Programming

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Balaji M ◽  
Chandrasekaran M ◽  
Vaithiyanathan Dhandapani
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Real Time ◽  
Learning Outcomes ◽  
Real World ◽  
Time Constraints ◽  
Network Simulator ◽  
Practical Applications ◽  
Rail Network ◽  
Knowledge Enhancement

A Novel Rail-Network Hardware with simulation facilities is presented in this paper. The hardware is designed to facilitate the learning of application-oriented, logical, real-time programming in an embedded system environment. The platform enables the creation of multiple unique programming scenarios with variability in complexity without any hardware changes. Prior experimental hardware comes with static programming facilities that focus the students’ learning on hardware features and programming basics, leaving them ill-equipped to take up practical applications with more real-time constraints. This hardware complements and completes their learning to help them program real-world embedded systems. The hardware uses LEDs to simulate the movement of trains in a network. The network has train stations, intersections and parking slots where the train movements can be controlled by using a 16-bit Renesas RL78/G13 microcontroller. Additionally, simulating facilities are provided to enable the students to navigate the trains by manual controls using switches and indicators. This helps them get an easy understanding of train navigation functions before taking up programming. The students start with simple tasks and gradually progress to more complicated ones with real-time constraints, on their own. During training, students’ learning outcomes are evaluated by obtaining their feedback and conducting a test at the end to measure their knowledge acquisition during the training. Students’ Knowledge Enhancement Index is originated to measure the knowledge acquired by the students. It is observed that 87% of students have successfully enhanced their knowledge undergoing training with this rail-network simulator.

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