0% Complete
صفحه اصلی
/
بیست و نهمین کنفرانس مهندسی برق ایران
Improving the Reliability of Multicore Embedded Systems through an Evolutionary-based Task Scheduling Approach
نویسندگان :
Athena Abdi
1
Hamid R Zarandi
2
1- K.N.Toosi University of Technology
2- Amirkabir University of Technology
کلمات کلیدی :
Multiprocessor embedded systems, Reliability, Power Consumption, Multi-objective optimization ,Evolutionary algorithm, Task scheduling.
چکیده :
In this paper, a task scheduling approach based on Strength Pareto Evolutionary algorithm (SPEA2) to improve the reliability of multi-core embedded systems is presented. Multi-core embedded systems are widely employed in many applications such as transportation, health-care, electricity grid and so on. Reliability is one of the major concerns of these systems due to its effect on lifetime of processors. To efficiently enhance reliability, its mutual impact on other design parameters such as performance and power consumption should be considered. Moreover, reliability in terms of soft and hard error rate is very important due to employing the embedded systems in safety-critical applications. The mentioned criteria are not independent and their joint optimization is associated with some complicated trade-offs. Considering these criteria at the system-level and optimize them during the task scheduling process, is one of the most effective methods. In this paper, we employ SPEA2 as a powerful evolutionary algorithm for solving the defined multi-objective optimization problem during task scheduling process. Thus, the order and place of executing each task of application are determined during the optimization process of the mentioned design criteria and based on the precedence limits. To demonstrate the effectiveness of our proposed method, several experiments are performed that check the ability of our approach in exploring the design space and meeting the existing trade-offs among the considered criteria during enhancing the processing system reliability. Moreover, the proposed method is compared to related studies in terms of design space exploration and joint optimization capability. Based on these experiments, our proposed method outperforms related studies and provides a more proper solution set based on the joint optimization of reliability, power consumption and performance.
لیست مقالات
لیست مقالات بایگانی شده
Optimal D2D Resource Allocation in Heterogeneous Cellular Networks by Decentralized Multi-Agent Deep Q-Learning
Pouya Akhoundzadeh - Ghasem Mirjalily - Mohammad taghi Sadeghi
Non-contact Radar Technology and Machine Learning for Automated Sleep Apnea-Hypopnea Syndrome Detection
ُSaman Faridsoltani - Mohaddeseh Sadeghi - Zahra Rahmani - Somayyeh Chamaani
Secret Sharing Implementation of Predictive Functional Control
Enayat Amiri - Mohammad Haeri - Saeed Adelipour
User Identification Based on Hand Geometrical Biometrics Using Media-Pipe
Sara Ghanbari - Zahra Parvin Ashtyani - Mehdi Tale Masouleh
Contrastive Learning Framework for fMRI Time-Series Classification in Left and Right Epilepsy Using Continues Wavelet Transform
Marzieh Soheili-nejad - Saeed Masoudnia - Hamid Soltanian-zadeh
Slice-Aware Resource Calendaring in Cloud-based Radio Access Networks
Zeinab Sasan - Siavash Khorsandi
بررسی و شبیه سازی اضافه ولتاژهای صاعقه در نیروگاه خورشیدی برق خراسان و ارائه سیستم حفاظتی مناسب
هادی علی آبادی - بهزاد کرمانی
Design Of Observer-Based Nonlinear Controller For Tracking Maximum Power Point In The Solar Cell
Kobra Siahi - Mohammad Reza Arvan - Vahid Behnamgol - Mahdi Mosayebi
ارائه روشی جهت بهبود عملکرد شبکههای بیسیم حسگر ناهمگون مبتنی بر برداشت انرژی
محمد فرشته حکمت - علیرضا کشاورز حداد
Model Predictive Control for Interconnected Systems with Communication Delays
Reza Mohammadikia - Mahsan Tavakoli-Kakhki
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.0.4