NDLI: Task assignment strategy for overloaded systems

Content Provider	IEEE Xplore Digital Library
Author	Bin Fu Broberg, J. Tari, Z.
Copyright Year	2003
Description	Author affiliation: Sch. of Comput. Sci. & Inf. Technol., RMIT Univ., Vic., Australia (Bin Fu; Broberg, J.; Tari, Z.)
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.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Simulation IEEE Commun. Soc
Starting Page	1119
Ending Page	1125
File Size	404159
Page Count	7
File Format	PDF
ISBN	076951961X
ISSN	15301346
DOI	10.1109/ISCC.2003.1214264
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-07-03
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Delay Load management Distributed computing Testing Exponential distribution Computer science Information technology Australia Performance evaluation Distribution strategy
Content Type	Text
Resource Type	Article
Subject	Signal Processing Mathematics Computer Networks and Communications Computer Science Applications Software

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