2026-09-19T01:46:46Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/50739 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Gupta, Indranil Alkaff, Hilfi 2014-09-16T17:26:03Z 2014-09-16T17:26:03Z 2014-08 2014-09-16 2014-08 Today, application schedulers are decoupled from routing level schedulers, leading to sub-optimal throughput for cloud computing platforms. In this thesis, we propose a cross-layer scheduling framework that bridges the application level scheduler with the routing level scheduler (SDN). We realize our framework in a batch-processing framework (Hadoop) and a stream-processing framework (Storm [2]). Our experimental results show that we are able to improve throughput of jobs in Storm and Hadoop by up to 32% and 29% respectively. Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2014-05-09T13:10:09Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Alkaff_Hilfi.pdf: 1297973 bytes, checksum: 4f5f3bb995c82f1f9e6a610191f3d169 (MD5) Made available in DSpace on 2014-09-16T17:26:03Z (GMT). No. of bitstreams: 2 Hilfi_Alkaff.pdf: 1297973 bytes, checksum: 4f5f3bb995c82f1f9e6a610191f3d169 (MD5) license.txt: 4061 bytes, checksum: 7100c3eab3cd6e6f2dc5a7957268e303 (MD5) http://hdl.handle.net/2142/50739 en Copyright 2014 Hilfi Alkaff Distributed System Software-Defined Networking Stream Processing Cross-layer scheduling in cloud computing systems text Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. MS:Computer Science -UIUC 10KS0112MS