A study on speculative task scheduling for apache spark in fog computing realms

Moysis Symeonides, Demetris Trihinas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Speculative task scheduling is a technique used by most of today’s distributed data processing systems to cope with slow running tasks that delay subsequent computations and hamper the overall performance of analytics jobs. Fog computing is now becoming a prominent service paradigm to foster applications with low-latency analytics requirements by moving the analysis closer to the data sources. However, task scheduling in fog realms is not without challenges, as resource heterogeneity and highly volatile network connections have the potential to delay instead of improving the completion time of analytics jobs. In this paper, we present a comprehensive study showcasing the various obstacles that are presented in speculative task scheduling for analytics jobs deployed in fog realms and derive critical insights that must be taken into account when introducing new task scheduling algorithms.

Original languageEnglish
Title of host publicationProceedings of the 23rd Pan-Hellenic Conference of Informatics, PCI 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450372923
DOIs
Publication statusPublished - 28 Nov 2019
Event23rd Pan-Hellenic Conference of Informatics, PCI 2019 - Nicosia, Cyprus
Duration: 28 Nov 201929 Nov 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference23rd Pan-Hellenic Conference of Informatics, PCI 2019
Country/TerritoryCyprus
CityNicosia
Period28/11/1929/11/19

Fingerprint

Dive into the research topics of 'A study on speculative task scheduling for apache spark in fog computing realms'. Together they form a unique fingerprint.

Cite this