Flux Research Group / School of Computing
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KnowOps: Network Management, Software Defined

Operational complexity counts 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. In short, research on network M&O has not kept pace with the research transforming the networks themselves. We identify three primary research challenges that stand in the way of improving M&O and designing systems for autonomic network M&O. The first is the lack of a holistic network-wide management framework that puts knowledge, policy, and practices into software, rather than in the hands of operators. The second is the fact that, despite the inherent structure present in networks, data from these networks are highly unstructured, semantically deficient and suffer from data uncertainty. Finally, though there is some understanding of how to set the myriad of discrete configuration options in a modern network individually, it is an open problem to set them dynamically on a network wide-basis, responding to changing conditions.

To address these deficiencies, we propose to realize a Knowledge-Centric Software-Defined Network Management and Operations architecture (KnowOps). We propose to create a network operations framework (NOF) as a systematic and principled foundation for comprehensive network management and operations. We 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. We plane to create a knowledge base capable of systematically capturing operational procedures and policies as specified by domain experts. Finally, we will develop search based policy execution strategies to allow the setting of network operating points to be optimized based on current network conditions.

current people

Ren Quinn
Ren Quinn
PhD student
Aisha Syed
Aisha Syed
PhD student
Josh Kunz
Josh Kunz
Masters student
Quinn Luck
Quinn Luck
Undergraduate student

alumni

Arijit Banerjee
Arijit Banerjee
Federated Wireless

publications

2017
Orchestrating the Data-plane of Virtual LTE Core Networks
Rajesh Mahindra, Arijit Banerjee, Karthik Sundaresan, Sneha Kumar Kasera, Jacobus (Kobus) Van der Merwe, and Sampath Rangarajan
In IEEE SECON 2017 [ pdf :: bibtex ]
SIMECA: SDN-based IoT Mobile Edge Cloud Architecture
Binh Nguyen, Nakjung Choi, Marina Thottan, and Jacobus (Kobus) Van der Merwe
In IFIP/IEEE International Symposium on Integrated Network Management - Mini Conference 2017 [ pdf :: bibtex ]
2016
2015
2014