IDAN Main Objectives, Phase II and III

Intent-Driven Autonomous Networks (IDAN) are a knowledge-centric automation mechanism designed to receive customer requirements and distribute them across the business, service, and resource operational layers. 

IDAN Phase III is based on the work done on last year’s IDAN phase II development. Before diving into Phase III, let’s review IDAN concepts and the work accomplished during Phase II. 

Examples of IDAN benefits include: 

Allowing the use of idle capacity that operators present in hours of low use of their networks. Transforming idle capacity into usable capacity based on intents 

Usually, the Operator´s networks or resources are not always at 100% utilization or occupation; there are periods when they are not used or have idle capacity. That is why this new model presents the option of being used based on attempts and transforming unused capacity into income or revenue. 

Enabling the participation of resellers (Brokers), where the same service can be offered at the best price, based on intents and selecting the best relation offer/price between the Network Operator´s offerings. As the user has the option of offering the price to pay for the service, third parties will be able to provide the broker service, looking for the best offer/price ratio between different operators by invoking various attempts. In this way, the final customer, instead of generating attempts to other operators, will only generate one intent to the broker, and it will search for the best option, reducing the complexity of the integration. 

Empowering the end user(s) to propose the price they want/can pay for the service. As mentioned above, the traditional model is based on the operator’s offer, and the final user can only choose between them. The strength of this model changes this way, where the customer offers through an intent including what he is willing to pay for a particular service and the operator will notify him when the desired service can be used.

Enhancing multi-vendor integration, as it is based on API standards. This model is based entirely on the use of standard APIs, defined with multi-company work groups, oriented to the new paradigm, and easy implementation. 

As outlined in IDAN phase II, dynamic pricing for connectivity service was achieved by the implementation of several objectives: 

  • Knowledge modeling with an extensible ontology 
  • TM Forum intent API (TMF921) – The new API proposed for this implementation. 
  • Existing artifacts, such as Service Orchestrators and Service Assurance Platforms 

The IDAN Catalyst integration and inception also demonstrate how existing systems, such as orchestrators and assurance solutions, interact with intent management. Intent does not require existing systems to replace their APIs

How does this work? 

Measurement: Determine the state of the system. This means continuous observations and measurements are made for every requirement in the intent. 

Assurance: Determine if the system meets the requirements as stated in the intent. Proposal: Find possible solutions. Multiple alternatives can be proposed. 

Evaluation: Decide what to do based on the proposed solutions and an evaluation of their utility for meeting intent requirements. 

Actuation: execute the solution that is expected to transition the system into a state of the best possible utility. 

IDAN’s phase III goal surrounds the concept of “Intent Conflict Resolution. “


As seen in the diagram above, the new concept of conflict and constraint management is analyzed, giving way to the Phase III goal of conflict resolution logic. 

To achieve this, some additional logic/modules needed to be added to phase II to achieve autonomous operation and decision-making for conflict management and resolution, such as: 

Machine Learning and AI Algorithms to make intelligent decisions. When conflicts occur, these algorithms can analyze historical data, network behavior patterns, and contextual information to prioritize and resolve conflicts based on learned insights. 

Reinforcement Learning techniques, where network elements, agents, or controllers learn from feedback and rewards to resolve conflicts. 

Distributed Consensus Mechanisms. As conflicts may arise when multiple autonomous agents or controllers make independent decisions, distributed consensus mechanisms, such as voting algorithms or consensus protocols can be employed to reach agreements. This ensures that conflicts are resolved based on a collective decision or by following predefined rules. 

Intent Negotiation and Collaboration Negotiate and collaborate to resolve conflicts. When conflicts occur, the involved entities can communicate, exchange intent information, and collaborate to find beneficial solutions.

Human Override, as the goal is to minimize human intervention, specific conflicts may require human expertise or judgment. This allows human operators to override autonomous decisions and provide manual conflict resolution based on their experience, situational awareness, or higher-level policies. 

It’s critical to remember that intent-driven autonomous networks are still evolving. Intraway and our partners are continuously working towards transforming the telecommunications industry – following the objective of maximizing the use of networks and the standardization of APIs so that integrations can be executed as quickly as possible! 

Discover the Power of Intent-Driven Autonomous Networks

Learn how AI, ML, and automation technologies can pave the way for a future of seamless, adaptive, and customer-centric telecommunications services. Download our white paper now


You may also like

Autonomous Networks

Intraway commits to TM Forum’s standards and best practices to speed the adoption of Autonomous Networks


5 Game-Changing Ways Intent Changes Provisioning, Activation, and Orchestration

Intent-Driven Autonomous Networks

Benefits of Intent-Driven Autonomous Networks