An Effective Task Scheduling Genetic Method of Power Aware Consideration for Real-Time Embedded Multiprocessor SOC Design

• Main Authors: Yen Hsiang Chang, 張雁翔
• Other Authors: Cheng Chen
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/26896878674087435037

碩士 === 國立交通大學 === 資訊工程系 === 90 === With the rapid evolution of submicron technology and the popularization of portable devices, embedded multiprocessor System-On-Chip (SOC) architecture will be one of the most attractive trends. How to decrease power consumption and process data in real-time is one of the most interesting topics to be investigated. The task scheduling is an important step through the whole process. In this thesis, we schedule tasks to obtain the minimal power consumption under time constraint, which is based on Genetic Algorithm. However, Genetic Algorithm needs huge computation time and therefore we propose an effective algorithm, named Constrained Genetic Method (CGM), by adding some constraints to Genetic Algorithm. Moreover, we partition the whole tasks graphs into several subgraphs to decrease computation time. But the total power consumption will increase after mergence process. Thus, we proposed a Power Minimization Method to decrease the total power consumption. The detail descriptions of our algorithm will be given in the contents.