意图驱动数据链网络策略协商模型与算法

Intent-driven data link network policy negotiation model and algorithm

针对意图驱动数据链网络中多条意图策略冲突问题,提出一种基于优先级的意图协商算法,实现网络资源受限条件下意图策略最优配置。所提算法综合考虑时间、带宽两个维度的资源,通过回收已配置低优先级意图资源间接增多可用的网络资源,提高待配置高优先级意图业务质量。同时,利用最优化求解得到待配置高优先级意图、被回收低优先级意图的最佳资源分配方式,避免意图因资源不足强行降级而导致服务质量急剧下降的问题。实验结果表明,所提算法提高了数据链网络资源规划能力,相较于已有的协商算法,在意图服务质量上有6.0%和5.5%的提升。

The priority based intent negotiation algorithm is proposed to address the issue of conflicting intent policies in intent-driven data-link networks.The algorithm aims to achieve the optimal configuration of intent policies while considering the limited availability of network resources.It takes into account both time and bandwidth dimensions of resources and indirectly increases the available network resources by reclaiming resources from low-priority intents that have already been configured.This approach enhances the quality of high-priority intents that are yet to be configured.Additionally,the algorithm utilizes optimization techniques to determine the best resource allocation for configuring high-priority intents and reclaiming low-priority intents,thereby avoiding the problem of forcefully downgrading intents due to insufficient resources and the resulting degradation in service quality.Experimental results demonstrate that the proposed algorithm significantly improves the resource planning capability of data-link networks,leading to a 6.0%and 5.5%enhancement in intent service quality compared to existing negotiation algorithms.