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A Novel Approach to Modelling Distributed Systems: Using Large-Scale Multi-agent Systems

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Software Project Management for Distributed Computing

Part of the book series: Computer Communications and Networks ((CCN))

Abstract

Large-scale multi-agent systems (LSMAS), a rather novel concept in the domain of multi-agent systems (MAS), are reaching for soaring heights in the wake of the Internet of Everything era. Interacting pieces of software on interconnected machines, enabled by rapid development of the Internet and connected devices, are creating systems comprising tens of thousands, even millions, of agents. Each agent is thus situated in an environment with numerous other elements, and interaction is inevitable. Such a situation benefits from organisational modelling of the system. Using an organisational metamodel, which provides concepts for definitions of several organisational models, introduces upgraded time and effort efficiency into LSMAS organisational modelling, thus aiding in cost and time efficiency of design and development of distributed software. This chapter introduces a novel method of LSMAS organisational modelling using an organisational metamodel which makes it easier to model an LSMAS at various levels of abstraction. The presented metamodel is a work-in-progress description based on an ontology being developed that comprises LSMAS organisational concepts. Some features of the metamodel are presented, in this chapter, using two distinct examples of LSMAS application domains. Main features differentiating the proposed metamodel from the existent LSMAS organisational models also include concepts for modelling interorganisational dynamics.

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This work has been supported in full by the Croatian Science Foundation under the project number 8537.

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Correspondence to Bogdan Okreša Ðurić .

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Okreša Ðurić, B. (2017). A Novel Approach to Modelling Distributed Systems: Using Large-Scale Multi-agent Systems. In: Mahmood, Z. (eds) Software Project Management for Distributed Computing. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-54325-3_10

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