Publication
Title
On the impact of job size variability on heterogeneity-aware load balancing
Author
Abstract
Load balancing is one of the key components in many distributed systems as it heavily impacts performance and resource utilization. We consider a heterogeneous system where each server belongs to one of K classes and the speed of the server depends on its class. Arriving jobs are immediately dispatched to a server class in a randomized manner, i.e., with probability pk a job is assigned to class k. Within each class a power of d choices rule is used to select the server that executes the job. For large systems and exponential job size durations the optimal probabilities pk to minimize the mean response time can be determined easily via convex optimization. In this paper we develop a mean field model (validated by simulation) to investigate how these optimal probabilities pk are affected by the higher moments and in particular by the variability of the job size distribution when the service discipline at each server is first-come-first-served. The main insight provided is that optimizing the probabilities pk based on the higher moments is much more involved and provides only a non negligible gain for very specific system load regions.
Language
English
Source (journal)
Lecture notes in computer science. - Berlin, 1973, currens
Source (book)
Queueing Theory and Network Applications : 13th International Conference, QTNA 2018, July 25-27, 2018Tsukuba, Japan / Takahashi, Yutaka [edit.]; et al.
Source (series)
Theoretical Computer Science and General Issues book sub series (LNTCS) ; 10932
Publication
Cham : Springer, 2018
ISBN
978-3-319-93735-9
Volume/pages
10932(2018), p. 193-215
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identification
Creation 13.12.2018
Last edited 15.07.2021
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