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Join-Up-To(m): improved hyperscalable load balancing.

Authors :
Kielanski, Grzegorz
Hellemans, Tim
Van Houdt, Benny
Source :
Queueing Systems. Dec2023, Vol. 105 Issue 3/4, p291-316. 26p.
Publication Year :
2023

Abstract

Various load balancing policies are known to achieve vanishing waiting times in the large-scale limit, that is, when the number of servers tends to infinity. These policies either require a communication overhead of one message per job or require job size information. Load balancing policies with an overhead below one message per job are called hyperscalable policies. While these policies often have bounded queue length in the large-scale limit and work well when the overhead is somewhat below one, they show poor performance when the communication overhead becomes small, that is, the mean response time tends to infinity when the overhead tends to zero even at low loads. In this paper, we introduce a hyperscalable load balancing policy, called Join-Up-To(m), that remains effective even when the communication overhead tends to zero. To study its performance under general job size distributions, we make use of the "queue at the cavity" approach. We provide explicit results for the first two moments of the response time, the generating function of the queue length distribution and the Laplace transform of the response time. These results show that the mean response time only depends on the first two moments of the job size distribution. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02570130
Volume :
105
Issue :
3/4
Database :
Academic Search Index
Journal :
Queueing Systems
Publication Type :
Academic Journal
Accession number :
173821521
Full Text :
https://doi.org/10.1007/s11134-023-09897-5