Computation Efficiency Driven Job Removal Policies for Meeting End-to-End Deadlines in Distributed Real-Time Systems

被引：0

作者：

Song, Miao ^{[1
]}

Li, Shuhui ^{[1
]}

Ren, Shangping ^{[1
]}

Hong, Shengyan ^{[2
]}

Hu, Xiaobo Sharon ^{[2
]}

机构：

[1] IIT, Dept Comp Sci, Chicago, IL 60616 USA

[2] Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46556 USA

来源：

2013 IEEE 16TH INTERNATIONAL SYMPOSIUM ON OBJECT/COMPONENT/SERVICE-ORIENTED REAL-TIME DISTRIBUTED COMPUTING (ISORC) | 2013年

关键词：

TASKS;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In distributed real-time systems, when resource cannot meet workload demand, some jobs have to be removed from further execution. The decision as to which job to remove directly influences the system computation efficiency, i.e., the ratio between computation contributed to successful completions of real-time jobs and total computation contributed to the execution of jobs that may or may not be completed. The paper presents two job removal policies which aim at maximizing system's computation efficiency for distributed real-time applications where the applications' end-to-end deadlines must be guaranteed. Experiments based on benchmark applications generated by TGFF [1] are conducted and compared with recent work in the literature. The results show clear benefits of the developed approaches - they can achieve as much as 2 0 % computation efficiency improvement.

引用

页数：8