Optimisation of dynamic, hybrid signal function networks

Sculthorpe, N. ORCID: 0000-0002-7244-0916 and Nilsson, H., 2009. Optimisation of dynamic, hybrid signal function networks. In: M. Morazán, P. Koopman and P. Achten, eds., Trends in Functional Programming Volume 9. Intellect, pp. 97-112. ISBN 9781841502779

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Functional Reactive Programming (FRP) is an approach to reactive programming where systems are structured as networks of functions operating on signals. FRP is based on the synchronous data-flow paradigm and supports both continuous-time and discrete-time signals (hybrid systems). What sets FRP apart from most other languages for similar applications is its support for systems with dynamic structure and for higher-order data-flow constructs. This raises a range of implementation challenges. This paper contributes towards advancing the state of the art of FRP implementation by studying the notion of signal change and change propagation in a setting of hybrid signal function networks with dynamic structure. To sidestep some problems of certain previous FRP implementations that are structured using arrows, we suggest working with a notion of composable, multi-input and multi-output signal functions. A clear conceptual distinction is also made between continuous-time and discrete-time signals. We then show how establishing change-related properties of the signal functions in a network allows such networks to be simplified (static optimisation) and can help reducing the amount of computation needed for executing the networks (dynamic optimisation). Interestingly, distinguishing between continuous-time and discrete-time signals allows us to characterise the change-related properties of signal functions more precisely than what we otherwise would have been able to, which is helpful for optimisation.

Item Type: Chapter in book
Creators: Sculthorpe, N. and Nilsson, H.
Publisher: Intellect
Date: 2009
ISBN: 9781841502779
Divisions: Schools > School of Science and Technology
Record created by: Richard Cross
Date Added: 13 Dec 2016 14:15
Last Modified: 09 Jun 2017 14:09
URI: https://irep.ntu.ac.uk/id/eprint/29354

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