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authorzhaoyh6 <zhaoyh6@asiainfo.com>2022-03-21 15:12:19 +0800
committerzhaoyh6 <zhaoyh6@asiainfo.com>2022-03-21 15:12:26 +0800
commitbfa2f026a638934d1b9e0dc06e2e76c56baba17b (patch)
tree8e087503007be889b5836fbe08d6059278bf3118 /docs
parentb44075625fe5d092e0f7048b254edc986dd26c0a (diff)
feat: modify docs_intent_based_network.rst for R10
Issue-ID: REQ-1075 Signed-off-by: zhaoyh6 <zhaoyh6@asiainfo.com> Change-Id: I9c93228e5b87d48bd7974e59d11adc6abfdba597
Diffstat (limited to 'docs')
-rw-r--r--docs/docs_intent_based_network.rst27
1 files changed, 18 insertions, 9 deletions
diff --git a/docs/docs_intent_based_network.rst b/docs/docs_intent_based_network.rst
index b29a9f04..088faffa 100644
--- a/docs/docs_intent_based_network.rst
+++ b/docs/docs_intent_based_network.rst
@@ -23,6 +23,15 @@ The target architecture of the Intent-Based Network is divided into a Intent
orchestration layer (hereinafter referred to as the Intent layer), a control
layer and a network layer.
+REQ-861 Smart Intent Guarantee - Intent Instance
+The new network applications, like E2E Slicing and CCVPN, provide different SLA services to customers. In this REQ, a scenario of intent guarantee is proposed to support the SLA requirements of users in run-time, as well as updating users’ intents. In R9, Intent instance will be developed to support the E2E Slicing and CCVPN.
+
+REQ-1074 Smart Intent Guarantee based on Closed-loop in R10
+In R10, the closed-loop will be developed to support the smart Intent E2E Slicing and CCVPN.
+
+REQ-1075 Network Services without Perception for Users based on IBN
+In R10, Network Services without perception for users based on IBN will be developed to support the E2E Slicing and CCVPN.
+
Abbreviations
-------------
@@ -54,12 +63,12 @@ Three NLP algorithms are considered to be applied in current solutions:
- BERT (Bidirectional Encoder Representations from Transformers):developed by researchers at Google AI Language. It has caused a stir in the Machine Learning community by presenting state-of-the-art results in a wide variety of NLP tasks. BERT’s key technical innovation is applying the bidirectional training of Transformer, a popular attention model, to language modelling.
Scope of Istanbul release
------------------------
-The scope for Istanbul developed in AAI focuses on Intent Instance Management
-
-The storage and management of AAI-based Intent Instance are realized in the R9 version.
-Intent Instance is created to save the users' real-time intent (network parameters) and connected service ID (CCNVPN service ID / E2E Slicing customer service intent ID) in AAI.
-
+-----------------------
+The scope for Istanbul developed in AAI focuses on Intent Instance Management
+
+The storage and management of AAI-based Intent Instance are realized in the R9 version.
+Intent Instance is created to save the users' real-time intent (network parameters) and connected service ID (CCNVPN service ID / E2E Slicing customer service intent ID) in AAI.
+
The user's intent is stored from the UUI or SO to the intent instance in the AAI, and then DCAE calls the intent instance in the AAI through the interface.
Impacted Modules for Honolulu
@@ -75,9 +84,9 @@ the natural language, which then sends the user input to the IBN component and d
the response information to the user. This process can be repeated several times
until the dialog completes and a new Intent is formed in the IBN component.
-Target of R9: support multiple usecase services, so it is not a sub-node of any usecase in AAI.
-
-The IBN will be expect to provide unawares service to users. Multiple usecases services could be changed by IBN instead of the users, so it should be an independent node in AAI.
+Target of R9: support multiple usecase services, so it is not a sub-node of any usecase in AAI.
+
+The IBN will be expect to provide unawares service to users. Multiple usecases services could be changed by IBN instead of the users, so it should be an independent node in AAI.
Functional Test Cases