Persistent And Scalable JADE: A Cloud based InMemory Multi-agent Framework

TL;DR

This paper introduces a novel in-memory persistence framework for multi-agent systems that enhances scalability and persistence, especially suited for dynamic cloud environments with frequently changing agent states.

Contribution

It presents a new scalable in-memory persistence framework for multi-agent systems, validated through prototypes demonstrating improved scalability over existing methods.

Findings

The proposed framework is more scalable than existing approaches.

It maintains a similar level of persistency as current methods.

Experimental results confirm effectiveness in cloud environments.

Abstract

Multi-agent systems are often limited in terms of persistenceand scalability. This issue is more prevalent for applications inwhich agent states changes frequently. This makes the existingmethods less usable as they increase the agent's complexityand are less scalable. This research study has presented anovel in-memory agent persistence framework. Two prototypeshave been implemented, one using the proposed solution andthe other using an established agent persistency environment.Experimental results confirm that the proposed framework ismore scalable than existing approaches whilst providing asimilar level of persistency. These findings will help futurereal-time multiagent systems to become scalable and persistentin a dynamic cloud environment.