Adaptive traffic management for high-capacity network architectures with smart services

具有智能服务的高容量网络架构的自适应流量管理

• 批准号: 311996-2011
• 负责人: Ganti, Sudhakar
• 金额: $ 1.02万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=571666
• 关键词: Adaptive; traffic; management; capacity; network

Network services are evolving from client-server based services to location and context-aware distributed services. Future smart services will use context and location to push information to user devices dynamically. With the rapid growth of these smart network services, it is important to adapt the network technology so that it can provide service agility over a secure scalable platform. Users of the future Internet will demand a secure, energy-efficient, self-manageable, and configurable network platform. The objective of our research program is to investigate methods and techniques at the network traffic management level to support smart services effectively. One of the most promising research approaches is to employ autonomic communications for network and device self-configuration, self-provisioning, and self-management. We will design dynamic resource management methods and algorithms by monitoring network resources. With ever increasing link speeds, it is a challenging problem to design routers and switching equipment that can cope with the high data rates of streaming audio and video. Our approach to this research problem is to investigate scalable packet based routing/switching architectures to transport such high volumes data effectively. Today's networks mostly detect spam, viruses, and other malicious network usage through dedicated end systems. High-speed backbone routers generally do not directly employ much intelligence to defend these. Our research group will develop methods and techniques to incorporate in-transit stateless designs in the backbone routers to detect malicious network usage as a network self-defence mechanism. Thus, our research will contribute highly efficient and secure methods, algorithms, and techniques to the critical area of future high capacity network architectures. This research is timely and of critical strategic importance for our nation. More autonomicity in networks will lead to simpler systems, better resiliency, more stability, higher availability, fewer errors, and higher security. Investigating methods and techniques at the network traffic management level is critical for the future of smart network service.

网络服务从基于客户端服务器的服务到位置和上下文感知的分布式服务不断发展。未来的Smart Services将使用上下文和位置动态地将信息推向用户设备。随着这些智能网络服务的快速增长，重要的是要调整网络技术，以便可以通过安全的可扩展平台提供服务敏捷性。未来的互联网用户将需要一个安全，节能，可自我管理和可配置的网络平台。我们的研究计划的目的是调查网络流量管理级别的方法和技术，以有效地支持智能服务。最有前途的研究方法之一是使用自主通信进行网络和设备自我配置，自我证明和自我管理。我们将通过监视网络资源来设计动态资源管理方法和算法。随着链接速度的不断提高，设计路由器和开关设备可以应对流媒体音频和视频的高数据速率是一个具有挑战性的问题。我们解决这一研究问题的方法是研究基于可扩展数据包的路由/切换体系结构，以有效地传输此类大量数据。当今的网络主要通过专用最终系统检测垃圾邮件，病毒和其他恶意网络使用。高速骨干路由器通常不会直接采用太多智力来捍卫这些智能。我们的研究小组将开发方法和技术，以在骨干路由器中纳入无状态设计，以将恶意网络用法视为网络自卫机制。因此，我们的研究将为未来的高容量网络体系结构的关键领域提供高效且安全的方法，算法和技术。这项研究对我们国家及时至关重要。网络中更多的自主性将导致更简单的系统，更好的弹性，更高的稳定性，更高的可用性，更少的错误和更高的安全性。在网络流量管理级别调查方法和技术对于智能网络服务的未来至关重要。