An Improved EDF Scheduling Algorithm Based on Fuzzy Inference Being Suitable for Embedded Soft Real-time Systems in the Uncertain Environments
EDF is a classic dynamic embedded real-time multitask scheduling algorithm. In an embedded soft realtime system, the deadline missing ratio is an important metric to evaluate system performance. When an embedded soft real-time system is overloaded, EDF algorithm is not effective. In addition, considering the unsteadiness and unpredictability of a practical task running environment due to the unsteadiness of network communication and the time estimation deviation, it is necessary to introduce fuzzy concept and theory to the scheduling field of embedded soft real-time application systems. In this paper, we proposed an improved fuzzy EDF scheduling model based on fuzzy inference which was more suitable for embedded soft real-time systems in an uncertain environment. In our scheduling model, all task are periodic and a tasks criticality and deadline distance are described with fuzzy set. In our scheduling algorithm, a tasks scheduling priority is gotten by looking up the inference rule table with its fuzzy deadline distance and fuzzy criticality patterns. Tasks with shorter fuzzy deadline distance and higher fuzzy criticality are scheduled first. The simulation test shows that our scheduling model has less deadline missing ratio than traditional EDF algorithm and the important tasks have less deadline missing ratio than that of others tasks in an overloaded uncertain embedded soft real-time system.
fuzzify deadline missing ratio fuzzy inference EDF.
Xian-Bo He
School of Computer Science,China West Normal University,NanChong,SiChuan,China
国际会议
The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)
沈阳
英文
588-592
2010-03-27（万方平台首次上网日期，不代表论文的发表时间）