Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.
Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Application-Awareness in Softwarized Networks: Building Intelligent Networks through Application and Network-Layer Collaboration
Abstract
Increasingly, campus networks manage a multitude of large-scale data transfers. Big data plays a pivotal role in university research and impacts engineering, agriculture, natural sciences, and humanities. Campus network infrastructures support multiple network management goals, including commodity internet traffic and high-performance networks for scientific research. These goals often impose conflicting requirements on network design and management, and therefore, networks optimized and specially engineered for data-intensive tasks are necessary. Further, many aspects of campus networks are hard to change without impacting regular network operation. Over the years, numerous solutions have focused on the management and security of large-scale data transfers. These solutions severely degrade data transfer performance or result in data flows completely bypassing the campus network management and security controls. This dissertation will study application-aware architectures and present software defined networking (SDN) and network functions virtualization (NFV) solutions for data-intensive science. Our proposed application-aware SDN solutions span network monitoring, management, service differentiation, and security for data-intensive applications. We first propose a novel application-aware architecture called SNAG (SDN-managed Network Architecture for GridFTP transfers). SNAG combines application-awareness with SDN-enabled network management to classify, monitor and manage network resources actively. At HCC, we also demonstrate how our system ensures the quality of service (QoS) for high-throughput workflows such as Compact Muon Solenoid (CMS) and Laser Interferometer Gravitational-Wave Observatory (LIGO). Next, we develop a novel application-aware flow reduction (AAFR) algorithm to optimally map service function chains (SFC) to multiple data centers while adhering to the data center’s capacity constraints. We then present an application-aware intelligent load balancing system for high-throughput, distributed computing workflows. Our solution integrates with a major U.S. CMS Tier-2 site. Lastly, by developing a scalable application-aware edge computing framework, we focus on building reliable service-to-service communication across distributed infrastructures using a service mesh architecture. By building application-aware architectures and evolving data-intensive applications to collaboratively and securely share application-layer metadata with the network-layer, we pave the way for intelligent networks that are secure, automated, dynamically composable and highly scalable.
Subject Area
Computer Engineering|Computer science
Recommended Citation
Nadig, Deepak, "Application-Awareness in Softwarized Networks: Building Intelligent Networks through Application and Network-Layer Collaboration" (2021). ETD collection for University of Nebraska-Lincoln. AAI28646963.
https://digitalcommons.unl.edu/dissertations/AAI28646963