Rethinking large-scale network management through the lens of neuroscience

从神经科学的角度重新思考大规模网络管理

• 批准号: EP/X019101/1
• 负责人: Luc Berthouze
• 金额: $ 25.78万
• 依托单位: University of Sussex
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX019101%2F1
• 关键词: Rethinking; large; scale; network; management

The ever-increasing demand in traffic and diversity of services, along with the growing complexity and heterogeneity of the infrastructure supporting their provision is presenting an important challenge to current approaches to the management of communication networks. In particular, it becomes increasingly difficult for network management systems to keep a complete and tractable picture of the state of computing/network resources and running services, and their interdependencies, which in turn makes it difficult to achieve optimal performance. This proposal aims to transform the way ICT networks are being conceptualised for management, by developing a data-driven characterisation of emerging dependencies between ICT components inspired by recent neuroscientific paradigms used to study the brain and allowing to capture and act upon the functional impact of complex and changing interactions across layers and processes. By releasing network operators from human intervention and/or manual application of domain expertise, this research paves the way for the development of automated processes that can scale up to the size, heterogeneity and complexity of future ICT infrastructures.

业务和服务多样性的不断增长的需求，沿着支持其提供的基础设施的日益增长的复杂性和异质性，对当前的通信网络管理方法提出了重要的挑战。特别地，网络管理系统越来越难以保持计算/网络资源和运行服务的状态以及它们的相互依赖性的完整和易处理的画面，这又使得难以实现最佳性能。该提案旨在改变ICT网络被概念化用于管理的方式，通过开发ICT组件之间新兴依赖关系的数据驱动特征，这些依赖关系受到最近用于研究大脑的神经科学范式的启发，并允许捕获和处理跨层和过程的复杂和不断变化的相互作用的功能影响。通过将网络运营商从人工干预和/或领域专业知识的手动应用中解放出来，这项研究为开发自动化流程铺平了道路，这些流程可以扩展到未来ICT基础设施的规模，异质性和复杂性。