Abstract
Network as a Service (NaaS) enables cloud customers to connect their distributed services across multiple clouds without relying exclusively on their infrastructures. The discovery of NaaS services remains challenging not only because of their scale and diversity but also because of the hidden constraints that cloud providers impose on these services at the networking layer. NaaS services are usually offered in the form of service bundles containing underlying services and constraints not requested by the customers. This creates undesirable dependencies and constraints that hamper portability, compatibility and interoperability across providers. The problem of service discovery becomes more challenging when these constraints are the main and first cause that prevents a customer’s request from being fulfilled. Without a mechanism that enables customers to identify these constraints and to adjust their requests accordingly, existing service discovery solutions are likely to fall short. We propose to complement existing service discovery solutions by not only identifying unmatched constraints but also recommending relaxing discovery requests to retrieve optimal and compliant services.
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Notes
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Property Declaration in the diagram.
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Our model enables to define other services’ actions.
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An L2 address is equivalent to a MAC address if Ethernet is the communication protocol used at the second communication Layer (L2).
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This algorithm and all details related to the source code are available at supplementarymaterials/Algorithms.
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Study materials are available at https://userstudy.com/25ad8jv6.
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Acknowledgment
This work was partially funded by a French national program via the public private partnership project ISChyO, \(\text {n}^{\circ }\) 192906122-RAPID.
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Jerbi, I. et al. (2023). Request Relaxation Based-on Provider Constraints for a Capability-Based NaaS Services Discovery. In: Indulska, M., Reinhartz-Berger, I., Cetina, C., Pastor, O. (eds) Advanced Information Systems Engineering. CAiSE 2023. Lecture Notes in Computer Science, vol 13901. Springer, Cham. https://doi.org/10.1007/978-3-031-34560-9_36
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