@inproceedings{f440cbc1a8d74a1f862efa517a8f77c9,
title = "Cross-layer scheduling in cloud systems",
abstract = "Today, cloud computing engines such as streamprocessing Storm and batch-processing Hadoop are being increasingly run atop software-defined networks (SDNs). In such cloud stacks, the scheduler of the application engine (which allocates tasks to servers) remains decoupled from the SDN scheduler (which allocates network routes). We propose 1 a new approach that performs cross-layer scheduling between the application layer and the networking layer. This coordinated scheduling orchestrates the placement of application tasks (e.g., Hadoop maps and reduces, or Storm bolts) in tandem with the selection of network routes that arise from these tasks. We present results from both cluster deployment and simulation, and using two representative network topologies: Fat-tree and Jellyfish. Our results show that cross-layer scheduling can improve throughput of Hadoop and Storm by between 26% to 34% in a 30-host cluster, and it scales well.",
keywords = "Cloud computing, Cross-layer, Hadoop, SDN, Storm",
author = "Hilfi Alkaff and Indranil Gupta and Leslie, {Luke M.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 IEEE International Conference on Cloud Engineering, IC2E 2015 ; Conference date: 09-03-2015 Through 12-03-2015",
year = "2015",
doi = "10.1109/IC2E.2015.36",
language = "English (US)",
series = "Proceedings - 2015 IEEE International Conference on Cloud Engineering, IC2E 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "236--245",
booktitle = "Proceedings - 2015 IEEE International Conference on Cloud Engineering, IC2E 2015",
address = "United States",
}