SLA-Aware Scheduling of Map-Reduce Applications on Public Clouds

X. Zeng, S. Garg, Z. Wen, P. Strazdins, Lizhe Wang, R. Ranjan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The recent need of processing BigData has led to the development of several Map-Reduce applications for efficient large scale processing. Due to on-demand availability of large computing resources, Public Clouds have become a natural host of these Map-Reduce applications. In this case, users need to decide which resources they need to rent to run their MapReduce cluster other than deployment or scheduling of mapreduce tasks itself. This is not a trivial task particularly when users may have performance constraints such as deadline and have several Cloud product types to choose with intention of not spending much money. Even though there are several existing scheduling systems, however most of them are not developed to manage the scheduling of Map-Reduce applications. That is, they do not consider things like the number of map and reduce tasks and slots per VM. This paper proposes a novel greedy scheduling algorithm (MASA) that considers the users constraints in order to minimize cost of renting Cloud resources while considering the user's budget and deadline constraints. The simulation results show 25-60% reduction cost in comparison to current methods by using our proposed algorithm.
Original languageEnglish
Title of host publication2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages655-662
Number of pages8
ISBN (Electronic)978-1-5090-4297-5
ISBN (Print)978-1-5090-4298-2
DOIs
Publication statusPublished - 26 Jan 2017
Event18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems - Sydney, Australia
Duration: 12 Dec 201614 Dec 2016
http://www.swinflow.org/confs/2016/hpcc/

Conference

Conference18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems
Abbreviated titleHPCC 2016
CountryAustralia
CitySydney
Period12/12/1614/12/16
Internet address

Fingerprint

Dive into the research topics of 'SLA-Aware Scheduling of Map-Reduce Applications on Public Clouds'. Together they form a unique fingerprint.

Cite this