DocumentCode :
1680493
Title :
Task assignment strategy for overloaded systems
Author :
Fu, Bin ; Broberg, James ; Tari, Zahir
Author_Institution :
Sch. of Comput. Sci. & Inf. Technol., RMIT Univ., Vic., Australia
fYear :
2003
Firstpage :
1119
Abstract :
Size-based load distribution approaches are proposed to deal with high variation of task size. One of the most critical problem of these approaches is that they do not consider task deadlines (which if not met may cause task starvation). This paper proposes an extension of our early work on dynamic load balancing [E.L. Hahne et al., June 2002, M. Mirhakkak et al., Aug. 2001, A.S. Tanenbaum, 1996] (called LFF) which takes the relative processing time of task of a task into account and dynamically assigns it to the fittest server with a lighter load and high processing capacity. LFF-PRIORITY dynamically computes the task size priority and task deadline priority and puts them in a priority based multi-section queue. The testing results clearly show that LFF-PRIORITY out performs existing load distribution strategies. More importantly, more than 80% of tasks meet their task deadlines under LFF-PRIORITY strategy.
Keywords :
queueing theory; telecommunication network management; telecommunication traffic; LFF-PRIORITY strategy; dynamic load balancing; multisection queue; overloaded systems; size-based load distribution approaches; task assignment strategy; Australia; Computer science; Delay; Distributed computing; Distribution strategy; Exponential distribution; Information technology; Load management; Performance evaluation; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers and Communication, 2003. (ISCC 2003). Proceedings. Eighth IEEE International Symposium on
ISSN :
1530-1346
Print_ISBN :
0-7695-1961-X
Type :
conf
DOI :
10.1109/ISCC.2003.1214264
Filename :
1214264
Link To Document :
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