DocumentCode :
3093692
Title :
Load sharing based on task resource prediction
Author :
Goswami, Kumar K. ; Iyer, Ravishankar K. ; Devarakonda, Murthy V.
Author_Institution :
Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
Volume :
2
fYear :
1989
fDate :
3-6 Jan 1989
Firstpage :
921
Abstract :
Predicted task resource usage provides a basis for developing two centralized load-sharing policies: MinQ and MinResp. Trace-driven simulations are used to compare MinQ and MinResp against Centex, an efficient centralized scheme. Experimental results show that the use of prediction makes MinQ and MinResp significantly less sensitive to the status update rate than Centex. Consequently, the proposed algorithms perform better than Centex at slower update rates and are capable of handling larger workloads. The prediction-based policies are also highly effective for load-sharing in environments with widely varying CPU requirements. Using a real trace file,with an equal number of large and small tasks, MinResp consistently produced mean response times that were 9% to 35% lower than those of Centex
Keywords :
supervisory programs; virtual machines; CPU requirements; Centex; MinQ; MinResp; centralized load-sharing policies; response times; status update rate; task resource usage prediction; trace driven simulations; trace file; Aerodynamics; Computational modeling; Delay; History; NASA; Predictive models; Processor scheduling; Production systems; Runtime; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences, 1989. Vol.II: Software Track, Proceedings of the Twenty-Second Annual Hawaii International Conference on
Conference_Location :
Kailua-Kona, HI
Print_ISBN :
0-8186-1912-0
Type :
conf
DOI :
10.1109/HICSS.1989.48103
Filename :
48103
Link To Document :
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