TinTiN: Travelling in time (if necessary) to deal with out-of-order data in streaming aggregation
Paper in proceedings, 2020

Cyber-Physical Systems (CPS) rely on data stream processing for high-throughput, low-latency analysis with correctness and accuracy guarantees (building on deterministic execution) for monitoring, safety or security applications.
The trade-offs in processing performance and results' accuracy are nonetheless application-dependent. While some applications need strict deterministic execution, others can value fast (but possibly approximated) answers.
Despite the existing literature on how to relax and trade strict determinism for efficiency or deadlines, we lack a formal characterization of levels of determinism, needed by industries to assess whether or not such trade-offs are acceptable.
To bridge the gap, we introduce the notion of D-bounded eventual determinism, where D is the maximum out-of-order delay of the input data.
We design and implement TinTiN, a streaming middleware that can be used in combination with user-defined streaming applications, to provably enforce D-bounded eventual determinism.
We evaluate TinTiN with a real-world streaming application for Advanced Metering Infrastructure (AMI) monitoring, showing it provides an order of magnitude improvement in processing performance, while minimizing delays in output generation, compared to a state-of-the-art strictly deterministic solution that waits for time proportional to D, for each input tuple, before generating output that depends on it.

Data streaming

Advanced Metering Infrastructure

Smart Meter

Author

Joris Van Rooij

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Vincenzo Massimiliano Gulisano

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Marina Papatriantafilou

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

DEBS 2020 - Proceedings of the 14th ACM International Conference on Distributed and Event-Based Systems

141-152

14th ACM International Conference on Distributed and Event-Based Systems
Montreal, Canada,

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Swedish Foundation for Strategic Research (SSF), 2016-01-01 -- 2020-12-31.

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HARE: Self-deploying and Adaptive Data Streaming Analytics in Fog Architectures

Swedish Research Council (VR), 2017-01-01 -- 2020-12-31.

STAMINA - WASP

Wallenberg AI, Autonomous Systems and Software Program, 2016-04-04 -- 2020-04-06.

STAMINA - GE

Göteborg Energi, Foundation for Research and Developmen, 2017-01-01 -- 2021-12-31.

Subject Categories

Computer Engineering

Computer Science

Computer Systems

Areas of Advance

Energy

DOI

10.1145/3401025.3401769

More information

Latest update

10/28/2020