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In-Network Scheduling for Real-Time Analytics

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Udayashankar_Sreeharsha.pdf (2.61 MB)

Date

2021-04-30

Authors

Udayashankar, Sreeharsha

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Publisher

University of Waterloo

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.

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Keywords

cloud computing, networking, in-network, scheduling, low latency

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Citation

URI

http://hdl.handle.net/10012/16922

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Theses
Computer Science