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Although policies are intrinsically related to services and the problems of policy refinement and service composition are similar, proposals to address both problems together are not common.
We propose a decision analytics approach that leverages adaptive learning in the refinement of service operations.
A key part of our proposal is the concept of service refinement, a combination of service composition, and policy refinement which involves refining a higher level service specification into an integrated composite of lower level services.
Successive refinement in resolving service names limits the scope of churn to ensure scalability, while in-band signaling of new addresses supports seamless communication as end-points move.
Figure 2 The service refinement cycle.
Two important underlying concepts in our proposal are the service refinement cycle and the service code.
The main reason for dividing service refinement into four phases is to provide separation of concerns.
By dividing a service refinement into pieces, we can expect service creation (manual or automated) to become easier.
Network convergence promotes the expansion, extension, and refinement of network service chain and the innovation of the industrial form.
However, technologies for the four phases of the service refinement cycle must be specified to create a running system.
Both are based on the service refinement cycle, generate services in the form of service code, and are based on a generic platform of a service creation tool, which makes the job of executing and comparing different approaches easier.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com