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Programming interactions in collective adaptive systems by relying on attribute-based communication

Journal article
Authors Yehia Abd Alrahman
Rocco De Nicola
Michele Loreti
Published in Science of Computer Programming
Volume 192
Issue June
ISSN 0167-6423
Publication year 2020
Published at Department of Computer Science and Engineering, Computing Science (GU)
Language en
Keywords Attribute-based communication, Collective-adaptive systems, Computing methodologies, Operational semantics, Process calculus
Subject categories Theoretical computer science


© 2020 Elsevier B.V. Collective adaptive systems are new emerging computational systems consisting of a large number of interacting components and featuring complex behaviour. These systems are usually distributed, heterogeneous, decentralised and interdependent, and are operating in dynamic and possibly unpredictable environments. Finding ways to understand and design these systems and, most of all, to model the interactions of their components, is a difficult but important endeavour. In this article we propose a language-based approach for programming the interactions of collective-adaptive systems by relying on attribute-based communication; a paradigm that permits a group of partners to communicate by considering their run-time properties and capabilities. We introduce AbC, a foundational calculus for attribute-based communication and show how its linguistic primitives can be used to program a sophisticated variant of the well-known problem of Stable Allocation in Content Delivery Networks. In our variant, content providers are assigned to clients based on collaboration and by taking into account the preferences of both parties in a fully anonymous and distributed settings. We also illustrate the expressive power of attribute-based communication by showing the natural encoding of group-based, publish/subscribe-based and channel-based communication paradigms into AbC.

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