Lachesis: A Middleware for Customizing OS Scheduling of Stream Processing Queries
Paper in proceeding, 2021

Data streaming applications in Cyber-Physical Systems enable high-throughput, low-latency transformations of raw data into value. The performance of such applications, run by Stream Processing Engines (SPEs), can be boosted through custom CPU scheduling. Previous schedulers in the literature require alterations to SPEs to control the scheduling through user-level threads. While such alterations allow for fine-grained control, they hinder the adoption of such schedulers due to the high implementation cost and potential limitations in application semantics (e.g., blocking I/O).

Motivated by the above, we explore the feasibility and benefits of custom scheduling without alterations to SPEs but, instead, by orchestrating the OS scheduler (e.g., using nice and cgroup) to enforce the scheduling goals. We propose Lachesis, a standalone scheduling middleware, decoupled from any specific SPE, that can schedule multiple streaming applications, run in one or many nodes, and possibly multiple SPEs. Our evaluation with real-world and synthetic workloads, several SPEs and hardware setups, shows its benefits over default OS scheduling and other state-of-the-art schedulers: up to 75% higher throughput, and 1130x lower average latency once such SPEs reach their peak processing capacity.

operating systems

stream processing



Dimitrios Palyvos-Giannas

Network and Systems

Gabriele Mencagli

University of Pisa

Marina Papatriantafilou

Network and Systems

Vincenzo Massimiliano Gulisano

Network and Systems

Middleware 2021 - Proceedings of the 22nd International Middleware Conference

978-1-4503-8534-3 (ISBN)

22nd International Middleware Conference (Middleware '21)
Virtual Event, Canada,

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Subject Categories

Computer Engineering

Computer Science

Computer Systems

Areas of Advance






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