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

Advanced Metering Infrastructure

Data streaming

Smart Meter


Joris Van Rooij

Chalmers, Data- och informationsteknik, Nätverk och system

Göteborg Energi AB

Vincenzo Massimiliano Gulisano

Chalmers, Data- och informationsteknik, Nätverk och system

Marina Papatriantafilou

Chalmers, Data- och informationsteknik, Nätverk och system

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


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


Göteborg Energi, Forskningsstiftelsen, 2017-01-01 -- 2021-12-31.

INDEED: Information and Data-processing in Focus for Energy Efficiency

Chalmers, 2020-01-01 -- .

Molnbaserade produkter och produktion (FiC)

Stiftelsen för Strategisk forskning (SSF) (GMT14-0032), 2016-01-01 -- 2020-12-31.

HAREN: Självdistribuerad och anpassningsbar dataströmningsanalys i dimman

Vetenskapsrådet (VR) (2016-03800), 2017-01-01 -- 2020-12-31.


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



Datavetenskap (datalogi)






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