The operational complexity of networks and the resulting operational expense (OPEX) count among the top challenges faced by network operators. This complexity arises, in part, because of the scale and continued growth of modern networks, the inherent complexity and intricate dependencies of the protocols that these networks run, and the increased expectations of network users due to the increasing importance that network connectivity and networked services play in society. This complexity has been heightened by recent developments that make networks much more dynamic, adding a whole new dimension to the complexities of network management and operations (M&O). The resulting state of affairs acts to impede the pace of innovation and change in networks. The research on network M&O has not kept pace with the research transforming the networks themselves.
This project addresses these issues by designing and building a Knowledge-Centric Software-Defined Network Management and Operations architecture (KnowOps). KnowOps will represent a significant step in moving M&O towards fully autonomic operation. The project will generalize database-like abstractions to create a network operations fabric (NOF) as a systematic and principled foundation for comprehensive network management and operations. The PIs will combine this foundation with information centric data mining methods to create a structured information base which captures, in a systematic manner, the status of the network and expose it to other network management functions. The end result will be a knowledge base capable of systematically capturing operational procedures and policies as specified by domain experts.
Network OPEX is a major challenge for continued penetration of digital technologies into application areas in the home and small business. The project will involve collaboration with a large, national network operator but also with a small, mostly rural carrier. Improved network management tools are particularly important for smaller regional operators serving cyber-disadvantaged communities, who often do not have the technical breadth and depth of larger operators, but who, nonetheless, face the same operational challenges.
