A task-sets generator for supporting the analysis of multi-agent systems under general purpose and real-time conditions

Calvaresi, Davide (Scuola Superiore Sant’Anna,Pisa, Italy; University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Albanese, Giuseppe (Universit`a Politecnica delle Marche, Ancona, Italy) ; Dubosson, Fabien (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Marinoni, Mauro (Scuola Superiore Sant’Anna,Pisa, Italy) ; Schumacher, Michael (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

The adoption of Multi-Agent Systems (MAS) is permeating Internet of Things (IoT) and Cyber-Physical Systems (CPS). Timing reliability of MAS is a daring challenge. The study of local task execution and negotiation of workloads are catalyzing considerable interest. By adopting techniques typical of Real-Times Systems (RTS), MAS’s ability to comply with strict timing constraints has been proven. However, a complete formalization is still missing, and some of the existing mathematical models introduce considerable pessimism in the performance analysis. Therefore, the need for tools supporting the study of the behavior of agent-based systems is rising. Particularly, the capability of systematic assessment and comparison of their performance. This paper presents a system to generate task-sets and operating scenarios, to support the study of timing reliability, behavior, and performance of MAS. The parameters required for such a generation are characterized by randomly extracted values (e.g., the number of agents, single agent utilization factors, and single task utilization factor). For each parameter, it is possible to select a given statistical distribution to be applied to user-defined ranges. In particular, logic, constraints, and dependencies characterizing the generation algorithm are detailed and framed in a functional work-flow. Moreover, such a system integrates a MAS simulator powered by both general-purpose and real-time algorithms, named MAXIMGPRT. Hence, the presented tool is also able to show the logs of the tested scenarios equipped with graphs to enable the performance analysis.

Conference Type:
full paper
Economie et Services
Institut Informatique de gestion
Stockholm, Sweden, 15 July 2018
Stockholm, Sweden
15 July 2018
14 p.
Published in:
Proceedings of the 1st International Workshop on Real-Time compliant Multi-Agent Systems co-located with the Federated Artificial Intelligence Meeting
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 Record created 2018-11-12, last modified 2020-10-27

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