Comparing perfomance abstractions for collective adaptive systems

IF 1.1 3区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal on Software Tools for Technology Transfer Pub Date : 2023-11-02 DOI:10.1007/s10009-023-00728-9

Maurizio Murgia, Riccardo Pinciroli, Catia Trubiani, Emilio Tuosto

引用次数: 1

Abstract

Abstract Non-functional properties of collective adaptive systems (CAS) are of paramount relevance practically in any application. This paper compares two recently proposed approaches to quantitative modelling that exploit different system abstractions: the first is based on generalised stochastic Petri nets, and the second is based on queueing networks. Through a case study involving autonomous robots, we analyse and discuss the relative merits of the approaches. This is done by considering three scenarios which differ on the architecture used to coordinate the distributed components. Our experimental results assess a high accuracy when comparing model-based performance analysis results derived from two different quantitative abstractions for CAS.

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比较集体自适应系统的性能抽象

摘要集体自适应系统(CAS)的非功能特性在实际应用中具有重要意义。本文比较了最近提出的两种利用不同系统抽象的定量建模方法:第一种是基于广义随机Petri网，第二种是基于排队网络。通过一个涉及自主机器人的案例研究，我们分析和讨论了这些方法的相对优点。这是通过考虑用于协调分布式组件的体系结构不同的三种场景来完成的。当比较基于模型的性能分析结果时，我们的实验结果评估了很高的准确性，这些分析结果来源于两种不同的CAS定量抽象。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal on Software Tools for Technology Transfer Computer Science-Information Systems

CiteScore

4.50

自引率

6.70%

发文量

期刊介绍： The International Journal on Software Tools for Technology Transfer (STTT) provides a forum for the discussion of all aspects of tools supporting the development of computer systems. It offers, above all, a tool-oriented link between academic research and industrial practice. Tool support for the development of reliable and correct computer-based systems is of growing importance, and a wealth of design methodologies, algorithms, and associated tools have been developed in different areas of computer science. However, each area has its own culture and terminology, preventing researchers from taking advantage of the results obtained by colleagues in other fields. Tool builders are often unaware of the work done by others, and thus unable to apply it. The situation is even more critical when considering the transfer of new technology into industrial practice.