Cross-layer scheduling in cloud computing systems

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Alkaff, Hilfi

Contributors dc:contributor

• Gupta, Indranil

• Distributed System
• Software-Defined Networking
• Stream Processing

Statement dc:rights

• Copyright 2014 Hilfi Alkaff

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/50739

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/50739