This paper describes Nancy, a Network Calculus (NC) library that allows users to perform complex min-plus and max-plus algebra operations efficiently. To the best of our knowledge, Nancy is the only open-source library that implements operations working on arbitrary piecewise affine functions, as well as to implement some of them (e.g. sub-additive closure and function composition). Nancy allows researchers to compute NC results using a straightforward syntax, which matches the algebraic one. Moreover, it is designed having computational efficiency in mind: it exploits optimizations of data structures, it uses inheritance to allow for faster algorithms when they are available (e.g., for specific subclasses of functions), and it is natively parallel, thus reaping the benefit of multicore hardware. This makes it usable to solve NC problems which were previously considered beyond the realm of tractable.

Nancy: an efficient parallel Network Calculus library

Raffaele Zippo;Giovanni Stea
2022-01-01

Abstract

This paper describes Nancy, a Network Calculus (NC) library that allows users to perform complex min-plus and max-plus algebra operations efficiently. To the best of our knowledge, Nancy is the only open-source library that implements operations working on arbitrary piecewise affine functions, as well as to implement some of them (e.g. sub-additive closure and function composition). Nancy allows researchers to compute NC results using a straightforward syntax, which matches the algebraic one. Moreover, it is designed having computational efficiency in mind: it exploits optimizations of data structures, it uses inheritance to allow for faster algorithms when they are available (e.g., for specific subclasses of functions), and it is natively parallel, thus reaping the benefit of multicore hardware. This makes it usable to solve NC problems which were previously considered beyond the realm of tractable.
2022
Zippo, Raffaele; Stea, Giovanni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1150861
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