In this paper we present a class of nested automata for the modelling of performance, availability, and reliability of software systems with hierarchical structure, which we call systems of systems. Quantitative modelling provides valuable insight into the dynamic behaviour of software systems, allowing non-functional properties such as performance, dependability and availability to be assessed. However, the complexity of many systems challenges the feasibility of this approach as the required mathematical models grow too large to afford computationally efficient solution. In recent years it has been found that in some cases a fluid, or mean field, approximation can provide very good estimates whilst dramatically reducing the computational cost. The systems of systems which we propose are hierarchically arranged automata in which influence may be exerted between siblings, between parents and children, and even from children to parents, allowing a wide range of complex dynamics to be captured. We show that, under mild conditions, systems of systems can be equipped with fluid approximation models which are several orders of magnitude more efficient to run than explicit state representations, whilst providing excellent estimates of performability measures. This is a significant extension of previous fluid approximation results, with valuable applications for software performance modelling.

Fluid Performability Analysis of Nested Automata Models

BORTOLUSSI, LUCA;
2015

Abstract

In this paper we present a class of nested automata for the modelling of performance, availability, and reliability of software systems with hierarchical structure, which we call systems of systems. Quantitative modelling provides valuable insight into the dynamic behaviour of software systems, allowing non-functional properties such as performance, dependability and availability to be assessed. However, the complexity of many systems challenges the feasibility of this approach as the required mathematical models grow too large to afford computationally efficient solution. In recent years it has been found that in some cases a fluid, or mean field, approximation can provide very good estimates whilst dramatically reducing the computational cost. The systems of systems which we propose are hierarchically arranged automata in which influence may be exerted between siblings, between parents and children, and even from children to parents, allowing a wide range of complex dynamics to be captured. We show that, under mild conditions, systems of systems can be equipped with fluid approximation models which are several orders of magnitude more efficient to run than explicit state representations, whilst providing excellent estimates of performability measures. This is a significant extension of previous fluid approximation results, with valuable applications for software performance modelling.
http://www.sciencedirect.com/science/article/pii/S1571066114000954
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11368/2830526
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