  The majority of high energy physics experiments rely on data acquisition and
hardware-based trigger systems performing a number of stringent selections
before storing data for offline analysis. The online reconstruction and
selection performed at the trigger level are bound to the synchronous nature of
the data acquisition system, resulting in a trade-off between the amount of
data collected and the complexity of the online reconstruction performed.
Exotic physics processes, such as long-lived and slow-moving particles, are
rarely targeted by online triggers as they require complex and nonstandard
online reconstruction, usually incompatible with the time constraints of most
data acquisition systems. The online trigger selection can thus impact as one
of the main limiting factors to the experimental reach for exotic signatures.
Alternative data acquisition solutions based on the continuous and asynchronous
processing of the stream of data from the detectors are therefore foreseeable.
Trigger-less data readout systems, paired with efficient streaming data
processing solutions, can provide a viable alternative. In this document, an
end-to-end implementation of a fully trigger-less data acquisition and online
processing system is discussed. An easily scalable and deployable
implementation of such an architecture is proposed, based on open-source
distributed computing frameworks capable of performing asynchronous online
processing of streaming data. The proposed schema can be suitable for
deployment as a fully integrated system for small-scale experimental apparatus,
or to complement the trigger-based data acquisition systems of larger
experiments. A muon telescope setup consisting of a set of gaseous detectors is
used as the experimental development testbed in this work, and a fully
integrated online processing pipeline deployed on cloud computing resources is
implemented and described.
