Structure and Behaviour of Virtual Organisation Breeding Environments

This paper provides an outline of a formal approach that we are developing for modelling Virtual Organisations (VOs) and their Breeding Environments (VBEs). We propose different levels of representation for the functional structures and processes that VBEs and VOs involve, which are independent of the specificities of the infrastructures (organisational and technical) that support the functioning of VBEs. This allows us to reason about properties of tasks performed within VBEs and services provided through VOs without committing to the way in which they are implemented.

💡 Research Summary

The paper presents a formal, infrastructure‑agnostic framework for modeling Virtual Organisations (VOs) and the Virtual Organisation Breeding Environments (VBEs) that give rise to them. Recognizing that existing approaches often intertwine business logic with specific technical platforms, the authors propose a three‑level abstraction that separates concerns while preserving the ability to reason about functional behaviour and quality attributes.

At the highest level, the VBE model captures the participating enterprises, their roles, the shared resource pool, and the governance policies that regulate collaboration. This level is expressed using a formal policy language that can be checked for consistency and completeness. The middle level models individual VOs that are instantiated within a VBE to achieve a concrete business objective. Here, the VO’s service portfolio, contractual agreements, and Service Level Agreements (SLAs) are specified as formal contracts, enabling verification of compliance with VBE‑wide policies. The lowest level describes the concrete tasks and processes that a VO executes. Each task is modeled with pre‑conditions, post‑conditions, resource requirements, execution time, and cost, using process algebra and state‑transition systems.

Crucially, the framework defines precise mapping rules between the three levels: VBE policies constrain VO contracts, and VO contracts constrain task scheduling and resource allocation. Because the models are expressed in mathematically rigorous languages (e.g., temporal logic, process algebra), they can be fed to model‑checking tools, simulators, or theorem provers to verify safety properties (no resource conflicts), liveness (tasks eventually complete), and QoS guarantees (SLA compliance).

The authors illustrate the approach with a manufacturing case study where several small firms collaborate to develop a new product. By constructing the VBE, VO, and task models, they automatically detect potential resource contention on a shared testing facility and identify SLA violations before deployment. The analysis suggests policy adjustments—such as priority re‑ranking and task re‑allocation—that resolve the conflicts without redesigning the underlying IT infrastructure.

The paper discusses several advantages of the proposed method. First, the separation of functional models from implementation details allows the same VO/VBE specification to be deployed on cloud, grid, or IoT platforms without modification. Second, formal verification provides a rigorous basis for guaranteeing security, reliability, and performance, which is especially valuable in dynamic, multi‑organizational settings. Third, the reusable models accelerate the creation of new VOs, as designers can compose existing task and contract fragments rather than starting from scratch.

Limitations are also acknowledged. Building and maintaining detailed formal models can be labor‑intensive, and ensuring consistency across the three abstraction levels may require sophisticated tool support. Integrating real‑time operational data to keep models up‑to‑date poses additional challenges, as does scaling verification techniques to very large VBEs with hundreds of participants.

In conclusion, the authors argue that their multi‑level, infrastructure‑independent formalism offers a solid foundation for the systematic design, analysis, and evolution of collaborative digital ecosystems. Future work will focus on automating model generation from enterprise architecture artifacts, developing runtime adaptation mechanisms that update models in response to environmental changes, and extending the verification infrastructure to support large‑scale simulation and performance prediction. The contribution lies in providing a clear, mathematically grounded pathway from high‑level collaboration policies down to executable task specifications, thereby enabling trustworthy, flexible, and scalable virtual organisations.