DocumentCode :
2787953
Title :
Analysis of Scheduling Algorithms with Reservations
Author :
Eyraud-Dubois, Lionel ; Mounie, Gregory ; Trystram, Denis
Author_Institution :
LIP, ENS Lyon
fYear :
2007
fDate :
26-30 March 2007
Firstpage :
1
Lastpage :
8
Abstract :
In this work, we analyze the problem of scheduling a set of independent jobs on a homogeneous parallel computer. This problem has been widely studied from both a theoretical perspective (complexity analysis, and predictability of scheduling algorithms) and practical side (schedulers in production systems). It is common for some processors of a cluster to become unavailable for a certain period of time corresponding to reservations. These reservations represent blocks of time and quantities of resources set assigned in advance for specific applications. We propose here to investigate the scheduling problem where there are restricted resource availabilities. Our main result is to provide a deep analysis for this problem (complexity, lower bounds and upper bounds) for several variants of list scheduling algorithms. More precisely, we show that the problem of scheduling with any reservations can not be approximated. This leads to the study of restricted versions of this problem where the amount of reservation is limited. Our analysis is based on an old bound of Graham for resource constraint list scheduling for which we propose a new simpler proof by considering the continuous version of this problem.
Keywords :
computational complexity; processor scheduling; resource allocation; cluster computing; computational complexity; homogeneous parallel computer; list scheduling algorithm; production system; restricted resource availability; Algorithm design and analysis; Application software; Availability; Concurrent computing; Grid computing; Processor scheduling; Production systems; Scheduling algorithm; Software tools; Upper bound; Parallel Tasks; Scheduling; cluster computing; list scheduling; reservations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Conference_Location :
Long Beach, CA
Print_ISBN :
1-4244-0910-1
Electronic_ISBN :
1-4244-0910-1
Type :
conf
DOI :
10.1109/IPDPS.2007.370304
Filename :
4228032
Link To Document :
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