Colorado State University
Future of networking is the future of Big Data, The.
Degree: PhD, Computer Science, 2019, Colorado State University
Scientific domains such as Climate Science, High Energy Particle Physics (HEP), Genomics, Biology, and many others are increasingly moving towards data-oriented workflows where each of these communities generates, stores and uses massive datasets that reach into terabytes and petabytes, and projected soon to reach exabytes. These communities are also increasingly moving towards a global collaborative model where scientists routinely exchange a significant amount of data. The sheer volume of data and associated complexities associated with maintaining, transferring, and using them, continue to push the limits of the current technologies in multiple dimensions - storage, analysis, networking, and security. This thesis tackles the networking aspect of big-data science. Networking is the glue that binds all the components of modern scientific workflows, and these communities are becoming increasingly dependent on high-speed, highly reliable networks. The network, as the common layer across big-science communities, provides an ideal place for implementing common services. Big-science applications also need to work closely with the network to ensure optimal usage of resources, intelligent routing of requests, and data. Finally, as more communities move towards data-intensive, connected workflows - adopting a service model where the network provides some of the common services reduces not only application complexity but also the necessity of duplicate implementations. Named Data Networking (NDN) is a new network architecture whose service model aligns better with the needs of these data-oriented applications. NDN's name based paradigm makes it easier to provide intelligent features at the network layer rather than at the application layer. This thesis shows that NDN can push several standard features to the network. This work is the first attempt to apply NDN in the context of large scientific data; in the process, this thesis touches upon scientific data naming, name discovery, real-world deployment of NDN for scientific data, feasibility studies, and the designs of in-network protocols for big-data science.
Advisors/Committee Members: Papadopoulos, Christos (advisor), Partridge, Craig (advisor), Pallickara, Shrideep (committee member), Ray, Indrakshi (committee member), Burns, Patrick J. (committee member), Monga, Inder (committee member).
Subjects/Keywords: Future Internet Architecture; Large Scientific Data; Networking for big data; Information Centric Networking; Big Science; Named Data Networking
to Zotero / EndNote / Reference
APA (6th Edition):
Shannigrahi, S. (2019). Future of networking is the future of Big Data, The. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/197325
Chicago Manual of Style (16th Edition):
Shannigrahi, Susmit. “Future of networking is the future of Big Data, The.” 2019. Doctoral Dissertation, Colorado State University. Accessed January 20, 2020.
MLA Handbook (7th Edition):
Shannigrahi, Susmit. “Future of networking is the future of Big Data, The.” 2019. Web. 20 Jan 2020.
Shannigrahi S. Future of networking is the future of Big Data, The. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2020 Jan 20].
Available from: http://hdl.handle.net/10217/197325.
Council of Science Editors:
Shannigrahi S. Future of networking is the future of Big Data, The. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/197325