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Towards declarative intent processing and conflict resolution in IBN
... In [26], [27], the authors propose a Prolog-based declarative model to describe intents for chaining Virtual Network Functions (VNFs), with the capability of automatically identifying and resolving certain types of conflicts between two intents. A different approach is considered in [28] where the authors describe a GUI-based system for users to express their intents that is also capable of detecting conflicts and makes up to ten attempts to automatically deal with detected conflicts while making the least amount of changes to previously deployed intents. ...
Todays enterprise networks wrestle with accommodating an ever-growing number of devices of different types, supporting increasingly demanding applications and ever more complex services, and protecting their users from sophisticated and disrupting cyber threats. In response, a proposed architectural approach for improving network management, referred to as Intent-Based Networking (IBN), has attracted significant attention. It is built on the premise that network operators specify network policies in natural language and the network correctly translates these spoken intents (e.g., policies) into proper device-specific configurations that are then deployed across the network to reliably act on the operators expressed intents. Unfortunately, IBN has not yet fully delivered on its promise of automated, fast, and reliable policy deployment, mainly due to the significant challenges that the reliance on methods from Natural Language Processing (NLP) or more recent techniques from Machine Learning (ML) and Artificial Intelligence (AI) poses for unambiguously and accurately translating the myriad of intents that operators can express in natural language into “trustworthy” device configurations. This paper uses LUMI, a recently designed end-to-end prototype of a system that allows operators “to manage their network by talking to the network”, as an illustrative case study. In particular, we use it to elaborate on the different functionalities such systems should have to realize IBNs vision of automating the fast deployment of policies. At the same time, we leverage LUMI to highlight the extra efforts that are required to ensure that the deployed policies can be entrusted to accurately express and execute the operators original intents.
To automate network operations and deployment of compute services, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as intents. To fulfill the intents, closed control-loop operations carry out required configurations and deployments without human intervention. Despite the fact that intents are fulfilled automatically, conflicts may arise between user's and service provider's intents due to limited resources availability. This triggers IDSM system to initialize an intent negotiation process among conflicting actors. Intent negotiation involves generating one or more alternate intents based on the current state of the underlying physical/virtual resources, which are then presented to the intent creator for acceptance or rejection. In this way, the quality of services (QoS) can be improved significantly by maximizing the acceptance rate of service requests in the scenario of limited resources. However, intent negotiation systems are still in their infancy. The available solutions are platform dependent which poses various challenges in their adoption to diverse platforms. The main focus of this work is to draft and evaluate a comprehensive and generic intent negotiation framework which can be used to develop intent negotiation solutions for diverse IDSM platforms. In this work, we have identified and defined various processes that are necessary for intent negotiation. Furthermore, a generic intent negotiation framework is presented representing interactions among the identified processes, while conflicting actors engage in the intent negotiation. The results demonstrated that the proposed intent negotiation framework increases the intent acceptance rate by up to 38 percent with processing overheads less than 10 percent.
Intent-Based Networking (IBN) is a novel networking pardigm that allows networks to be autonomously configured, continuously assured, and to be highly adaptable to high-level intentions of network users and operators. In IBN systems, conflict detection and policy resolution modules are crucial to intent activation to enforce correct network configurations. To this end, in this study, we propose an extensible intent model, complemented with a conflict detection algorithm. We also propose a policy resolution algorithm that is based on a two-dimensional analysis of intent endpoints and time spans. To better showcase the efficiency of our algorithm, we also developed an enterprise-based IBN intent management web application for network users and administrators. Our evaluation experiments reveal the effectiveness of our algorithms in terms of reliable resolutions and fast response time.
Current and future network services and applications are expected to revolutionize our society and lifestyle. At the same time, the abundant possibilities that new network technologies offer to end users, network operators and administrators have created a cumbersome network configuration process to accommodate all different stakeholders and applications. Thus, lately, there is a need to simplify the management and configuration of the network, through possibly an autonomic and automatic way. Intent Based Networking (IBN) is such a paradigm that envisions flexible, agile, and simplified network configuration with minimal external intervention. This paper provides a detailed survey of how the IBN concept works and what are the main components to guarantee a fully autonomous IBN system (IBNS). Particular emphasis is given on the intent expression, intent translation, intent resolution, intent activation and intent assurance components, which form the closed loop automation system of an IBNS. The survey concludes with identifying open challenges and future directions of the problem at hand.
Developing and releasing multiservice applications rely upon a pipeline of automation tools known as Continuous Integration/Continuous Deployment. Among those tools, continuous reasoning is exploited by large companies to perform incremental static analyses on their code commits as soon as they are integrated into a shared codebase. In this article, we extend continuous reasoning towards the continuous QoS- and context-aware management of multiservice applications in Cloud-IoT scenarios. We propose a novel continuous reasoning methodology that supports runtime decision on service placement by reacting both to changes in the infrastructure and in the application requirements, and capable of suggesting migrations only for services affected by such changes. The methodology is prototyped in Prolog and assessed through simulations over a realistic use case and over a lifelike motivating scenario at increasing infrastructure sizes. Experimental results show that our approach brings considerable speed-up in comparison with an exhaustive search employing non-incremental reasoning.
Intent-Based Networking - Concepts and Definitions
- Clemm L Ciavaglia
- L Z Granville
- J Tantsura