2026-09-18T19:10:51Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/45663 2023-07-11 col_2142_5131 col_2142_16359 com_2142_5130 com_2142_16358 com_2142_234

Restriction data tranferred 2014-07-01T11:36:32-05:00 Original Data Group with Access Administrator Release Date: 2015-08-22 11:57:26 UTC Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system Item marked as restricted to the 'Administrator' Group (id=1) by Seth Robbins (srobbins@illinois.edu) on 2013-08-22T16:57:39Z Item is restricted until 2015-08-22T16:57:26Z Limited Restriction Lifted for Item 45645 on 2015-08-22T10:00:51Z. http://hdl.handle.net/2142/45663 en Copyright 2013 Faraz Faghri Performance of systems Service Level Objectives Fault tolerance Cloud computing Beck, Carolyn L. Faghri, Faraz 2013-08-22T16:57:06Z 2013-08-22T16:57:06Z 2015-08-22T10:00:51Z 2013-08 2013-08-22T16:57:06Z 2013-08 Increasingly, large systems and data centers are being built in a 'scale out' manner, i.e. using large numbers of commodity hardware components, instead of traditional 'scale up' using expensive, specialized equipment. However, large numbers of commodity components imply higher rates of failure across such systems. Such failures can cause applications to miss their deadlines for task completion. For this reason, cloud service providers and cloud applications must anticipate failures and engineer their services accordingly. In this thesis, we first analyze the availability of a commodity data center designed for MapReduce applications. MapReduce is increasingly used in industry for efficient large scale data processing tasks including personal advertising, spam detection, as well as data mining. We show how MapReduce software level fault tolerance can be used to achieve the same availability as scale up data centers. Second, we extend existing job schedulers for deadline-driven jobs to handle machine and software failures and satisfy the service level objectives. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-07-19T21:03:25Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Faghri_Faraz.pdf: 589342 bytes, checksum: 05d7992c02303a69df46065f1ccc191c (MD5) Made available in DSpace on 2013-08-22T16:57:06Z (GMT). No. of bitstreams: 2 Faraz_Faghri.pdf: 589342 bytes, checksum: 05d7992c02303a69df46065f1ccc191c (MD5) license.txt: 4061 bytes, checksum: 9366aeb0150eeee854116f9757adf479 (MD5) Hadoop MapReduce Performance guarantees for deadline-driven MapReduce jobs under failure text Industrial & Enterprise Systems Engineering 1422 Industrial Engineering 0127 University of Illinois at Urbana-Champaign Thesis M.S. MS:Industrial Engineerng -UIUC 10KS0127MS