意图驱动数据链网络策略协商模型与算法

doi:10.12305/j.issn.1001-506X.2024.06.31

摘要/Abstract

摘要：

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。

关键词: 意图驱动网络, 资源分配, 意图协商, 网络架构, 数据链网络

Abstract:

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.

Key words: intent-driven network, resource allocation, intent negotiation, network architecture, data link network

中图分类号:

TN919

刘祥林, 杨春刚, 李富强, 欧阳颖, 宋延博. 意图驱动数据链网络策略协商模型与算法[J]. 系统工程与电子技术, 2024, 46(6): 2128-2137.

Xianglin LIU, Chungang YANG, Fuqiang LI, Ying OUYANG, Yanbo SONG. Intent-driven data link network policy negotiation model and algorithm[J]. Systems Engineering and Electronics, 2024, 46(6): 2128-2137.

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参考文献 30

1	DANIELE,TSCHORSCHF.Ipfs and friends: a qualitative comparison of next generation peer-to-peer data networks[J].IEEE Communications Surveys & Tutorials,2022,24(1):31-52.
2	HAN Y, LI J, HOANG D, et al. An intent-based network virtualization platform for SDN[C]//Proc. of the 12th International Conference on Network and Service Management, 2016.
3	张露露,杨春刚,王栋,等.意图驱动的云网融合按需编排[J].电信科学,2022,38(10):107-119. doi: 10.11959/j.issn.1000-0801.2022272
	ZHANGL L,YANGC G,WANGD,et al.Intent-driven cloud-network convergence on-demand orchestration[J].Telecommunications Science,2022,38(10):107-119. doi: 10.11959/j.issn.1000-0801.2022272
4	PANGL,YANGC G,CHEND Y,et al.A survey on intent-driven networks[J].IEEE Access,2020,8,22862-22873. doi: 10.1109/ACCESS.2020.2969208
5	ZHANG H D, WANG Y, QI X T, et al. Demo abstract: an intent solver for enabling intent-based SDN[C]//Proc. of the IEEE Conference on Computer Communications Workshops, 2017: 968-969.
6	ELKHATIB Y, COULSON G, TYSON G. Charting an intent driven network[C]//Proc. of the 13th International Conference on Network and Service Management, 2017.
7	SUBRAMANYA T, RIGGIO R, RASHEED T. Intent-based mobile backhauling for 5G networks[C]//Proc. of the 12th International Conference on Network and Service Management, 2016: 348-352.
8	ESPOSITO F, WANG J, CONTOLI C, et al. A behavior-driven approach to intent specification for software-defined infrastructure management[C]//Proc. of the IEEE Conference on Network Function Virtualization and Software Defined Networks, 2018.
9	JACOBS A S, PFITSCHER R J, FERREIRA R A, et al. Refining network intents for self-driving networks[C]//Proc. of the Afternoon Workshop on Self-Driving Networks, 2018: 15-21.
10	PRAKASHC,LEEJ,TURNERY,et al.PGA: using graphs to express and automatically reconcile network policies[J].ACM SIGCOMM Computer Communication Review,2015,45(4):29-42. doi: 10.1145/2829988.2787506
11	SOULE R, BASU S, MARANDI P J, et al. Merlin: a language for provisioning network resources[C]//Proc. of the 10th ACM International on Conference on emerging Networking Experiments and Technologies, 2014: 213-226.
12	ABHASHKUMAR A, KANG J M, BANERJEE S, et al. Supporting diverse dynamic intent-based policies using Janus[C]// Proc. of the 13th International Conference on emerging Network- ing Experiments and Technologies, 2017: 296-309.
13	冯哲荟子. 支持多类策略的意图网络设计[D]. 成都: 电子科技大学, 2019.
	FENG Z H Z. Design of diverse policies supported intent-based net-working[D]. Chengdu: University of Electronic Science and Technology of China, 2019.
14	TENG Y, SHEN Y F, YANG H, et al. Conflict-driven intention negotiation based on reinforcement learning in intent defined optical networks[C]//Proc. of the 27th OptoElectronics and Communications Conference and 2022 International Confe-rence on Photonics in Switching and Computing, 2022.
15	徐丹,白燕南,王峰,等.意图网络研究综述[J].电子技术应用,2021,47(9):9-15.
	XUD,BAIY N,WANGF,et al.Survey of intent based networking[J].Application of Electronic Technique,2021,47(9):9-15.
16	WESTERINENA,SCHNIZLEINJ,STRASSNERJ,et al.Terminology for policy-based management[J].Reston: The Internet Society,2001,
17	KERNS,BAUMERT,GROLLS,et al.Optimization of access control policies[J].Journal of Information Security and Applications,2022,70,103301. doi: 10.1016/j.jisa.2022.103301
18	吴德春. 面向意图驱动网络的意图转译和智能优化研究[D]. 成都: 电子科技大学, 2022.
	WU D C. Research on intent translation and intelligent optimization for intent-driven networks[D]. Chengdu: University of Electronic Science and Technology of China, 2022.
19	KIRANM,POUYOULE,MERCIANA,et al.Enabling intent to configure scientific networks for high performance demands[J].Future Generation Computer Systems,2018,79,205-214. doi: 10.1016/j.future.2017.04.020
20	MAL,WENX M,WANGL H,et al.An SDN/NFV based framework for management and deployment of service based 5G core network[J].China Communications,2018,15(10):86-98. doi: 10.1109/CC.2018.8485472
21	FANIBHAREV,SARKARN I,AL-ANBUKYA.A survey of the tactile internet: design issues and challenges, applications, and future directions[J].Electronics,2021,10(17):2171. doi: 10.3390/electronics10172171
22	OUYANGY,YANGC G,SONGY B,et al.A brief survey and implementation on refinement for intent-driven networking[J].IEEE Network,2021,35(6):75-83. doi: 10.1109/MNET.001.2100194
23	ZHANG L L, YANG C G, OUYANG Y, et al. ISFC: Intent-driven service function chaining for satellite networks[C]//Proc. of the 27th Asia Pacific Conference on Communications, 2022: 544-549.
24	COMER D, RASTEGATNIA A. OSDF: an intent-based software defined network programming framework[C]//Proc. of the IEEE 43rd Conference on Local Computer Networks, 2018: 527-535.
25	LERNERA,SKORUPAJ,GANGULIS.Innovation insight: intent-based networking systems[J].Technology Reports,2017,66(8):28-36.
26	SHARMAY,BHAMARED,KASSLERA,et al.Intent negotiation framework for intent-driven service management[J].IEEE Communications Magazine,2023,61(6):73-79. doi: 10.1109/MCOM.001.2200504
27	MARSICOA,SAVIM,SIRACUSAD,et al.An automated negotiation framework for application-aware transport network services[J].Optical Switching and Networking,2020,38,100571. doi: 10.1016/j.osn.2020.100571
28	ZHONG Z Z, LI J P, HUA N, et al. On QoS-assured degraded provisioning in service-differentiated multi-layer elastic optical networks[C]//Proc. of the IEEE Global Communications Conference, 2016.
29	SANTOSA S,DE SANTIJ,FIGUEIREDOG B,et al.Application- aware service degradation in elastic optical networks[J].IEEE Trans.on Network and Service Management,2022,19(2):949-961. doi: 10.1109/TNSM.2022.3154331
30	KNIGHTS,NGUYENH X,FALKNERN,et al.The internet topology zoo[J].IEEE Journal on Selected Areas in Communications,2011,29(9):1765-1775. doi: 10.1109/JSAC.2011.111002

研究名称	动态性	应用场景	特点
PGA	静态策略	企业网络	直观的图形抽象来表达和组合网络策略
Janus	动态策略	异构网络	在某一时间段减少某些意图的带宽, 并在未来某一时刻进行补偿
INDIRA	动态策略	软件定义网络	为待协商意图分配网络所能提供的最大物理资源
ICRL	动态策略	软件定义光网络	在资源紧张时期为保证成功执行意图为待协商提供较低的网络资源
TBN	动态策略	IDN	选择协商时间片集合进行意图时间迁移及可用最大带宽的方式协商

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