dc.contributor.author | Udayashankar, Sreeharsha | |
dc.date.accessioned | 2021-04-30 15:20:44 (GMT) | |
dc.date.available | 2023-05-01 04:50:04 (GMT) | |
dc.date.issued | 2021-04-30 | |
dc.date.submitted | 2021-04-27 | |
dc.identifier.uri | http://hdl.handle.net/10012/16922 | |
dc.description.abstract | This thesis presents Bolt, a novel scheduler design for large-scale real-time data analytics. Bolt achieves the scheduling accuracy of modern centralized schedulers while supporting clusters with hundreds of thousands of nodes. At Bolt’s core is a scheduler design that leverages modern programmable switches. Bolt supports a FIFO scheduling policy, as well as task priority-based and task resource constraint-based scheduling policies.
Evaluation of a Bolt prototype on our cluster with a Barefoot Tofino switch shows that the proposed approach can reduce scheduling overhead by 40x and increase the scheduling throughput by 50x compared to state-of-the-art centralized and decentralized schedulers. | en |
dc.language.iso | en | en |
dc.publisher | University of Waterloo | en |
dc.subject | cloud computing | en |
dc.subject | networking | en |
dc.subject | in-network | en |
dc.subject | scheduling | en |
dc.subject | low latency | en |
dc.title | In-Network Scheduling for Real-Time Analytics | en |
dc.type | Master Thesis | en |
dc.pending | false | |
uws-etd.degree.department | David R. Cheriton School of Computer Science | en |
uws-etd.degree.discipline | Computer Science | en |
uws-etd.degree.grantor | University of Waterloo | en |
uws-etd.degree | Master of Mathematics | en |
uws-etd.embargo.terms | 2 years | en |
uws.contributor.advisor | Al-Kiswany, Samer | |
uws.contributor.affiliation1 | Faculty of Mathematics | en |
uws.published.city | Waterloo | en |
uws.published.country | Canada | en |
uws.published.province | Ontario | en |
uws.typeOfResource | Text | en |
uws.peerReviewStatus | Unreviewed | en |
uws.scholarLevel | Graduate | en |