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

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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.