標題: Event-driven dynamic workload scaling for uniprocessor real-time embedded systems
作者: Chang, Li-Pin
Chen, Ya-Shu
資訊工程學系
Department of Computer Science
關鍵字: embedded systems;real-time systems;adaptive applications;overload management;real-time surveillance
公開日期: 1-Sep-2007
摘要: Many embedded systems are designed to take timely reactions to the occurrences of particular scenarios. Such systems could sometimes experience transient overloads because of workload bursts or hardware malfunctions. Thus a mechanism to focus limited resources on the processing of urgent events is a key to retain system validity under stressing workloads. In this paper, we propose a new approach for workload Scaling in uniprocessor real-time embedded systems. The idea is to view the system as a black box, and workload scaling for overload management can be done via very intuitive primitives, i.e., how hardware events are selectively fed into the system. Such a new approach removes the need for the adjustments of task periods and task phasing, which is important for many workload-scaling techniques. The proposed approach is implemented in a real-time surveillance system. Experimental results show that the system still delivers good accuracy and high responsiveness for visual-object tracking under the presence of overloads.
URI: http://hdl.handle.net/11536/4241
ISSN: 1016-2364
期刊: JOURNAL OF INFORMATION SCIENCE AND ENGINEERING
Volume: 23
Issue: 5
起始頁: 1349
結束頁: 1365
Appears in Collections:Conferences Paper


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